https://wiki-ms.microbe-ms.com/api.php?action=feedcontributions&feedformat=atom&user=LaschpMicrobeMS Wiki - User contributions [en]2026-05-16T22:35:07ZUser contributionsMediaWiki 1.39.2https://wiki-ms.microbe-ms.com/index.php?title=Wilcoxon_Rank-Sum_Tests&diff=1212Wilcoxon Rank-Sum Tests2026-05-01T15:54:39Z<p>Laschp: Created page with "__FORCETOC__ == Introduction == input parameters for univariate t-tests| [https://en.wikipedia.org/wiki/Mann-Whitney_U_test Wilcoxon rank-sum test] (Wikipedia) To be continued (2026) == Parameter of Wilcoxon rank-sum tests == * '''m/z range''': lower and upper bounds of the m/z region in which the series of Wilcoxon rank-sum tests are to be performed * '''&alpha;''': significance level of the Wilcoxon rank-sum tests * '''''dx''''' (ppm): a..."</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|input parameters for univariate t-tests|]]<br />
<br />
[https://en.wikipedia.org/wiki/Mann-Whitney_U_test Wilcoxon rank-sum test] (Wikipedia)<br />
<br />
To be continued (2026)<br />
<br />
== Parameter of Wilcoxon rank-sum tests ==<br />
<br />
* '''m/z range''': lower and upper bounds of the m/z region in which the series of Wilcoxon rank-sum tests are to be performed<br />
* '''&alpha;''': significance level of the Wilcoxon rank-sum tests<br />
* '''''dx''''' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th<br />
* '''use intensities''': defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs<br />
* '''show histogram''': shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables<br />
<br />
== Performing Wilcoxon rank-sum tests ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pulldown menu.<br />
<br />
2. Wilcoxon rank-sum tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' &rarr; ''class X'' from the ''Edit'' pulldown menu.<br />
<br />
3. The test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing|spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the Wilcoxon rank-sum test function.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''peak frequency plots'' from the ''Analysis'' pulldown menu. Choose options ''from selection'' or ''from class X'' if the peak frequency test should involve selected spectra or spectra with an appropriate class labeling, respectively.<br />
<br />
== Output of Wilcoxon rank-sum test ==<br />
<br><br />
Example of the output from a series of Wilcoxon rank-sum tests taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:Wilcox-cmdln-output.png|576px|thumb|Command line output of Wilcoxon-tests. In this example, the m/z segment centered around 2518.0283 Th shows the greatest potential for distinguishing between classes I and II.]]<br />
|[[File:Wilcox-test-plot.jpg|400px|thumb|Plot of p-values (log scaled) obtained by Wilcoxon rank-sum tests using peak data from individual m/z segments as inputs: The smaller the p-value, the higher the discriminative potential of biomarker peaks at the specific m/z positions]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=MicrobeMS_-_A_Matlab_Toolbox_for_Microbial_Identification_Based_on_Mass_Spectrometry&diff=1211MicrobeMS - A Matlab Toolbox for Microbial Identification Based on Mass Spectrometry2026-05-01T15:53:59Z<p>Laschp: /* Identification of MS Biomarker Peaks */</p>
<hr />
<div>== Introduction ==<br />
<br />
The MicrobeMS software package is a program specifically designed for the analysis of MALDI-ToF mass spectra of microbial samples. The software was developed by [http://www.peter-lasch.de: Peter Lasch] at the [https://www.rki.de Robert-Koch-Institute (RKI)] in Berlin/Germany and can be used to identify microbial species based on their mass spectral patterns. The program is a comprehensive [http://www.mathworks.com: Matlab]-based package that operates under Windows 7/8/8.1/10/11 and LINUX (Debian, MicrobeMS versions later than 0.81). Original MALDI-ToF mass spectra in the format defined by [http://www.bdal.com: Bruker Daltonics] or by [http://www.shimadzu.com: Shimadzu] (via the mzXML data format) can be imported, processed and converted into a Matlab data matrix format specific to the MicrobeMS program.<br />
<br />
The software allows standard mass spectrometry manipulations such as smoothing, baseline correction, normalization, peak detection, auto-calibration to mention some preprocessing functions. Furthermore, functionalities of the software include, among others, microbial identification analysis based on spectral distances and machine learning methods (ML), e.g. by artificial neural networks (ANN) with visualization of the identification results, unsupervised hierarchical cluster analysis, biomarker analysis, pseudo-gel view generation, as well as microbial mass spectra database management including interfaces for organizing mass spectral metadata. Since the software also runs in a full Windows, or LINUX, 64-bit environment, the number of spectra in the data sets is limited only by the amount of available memory (RAM).<br><br />
<br />
== Getting Started ==<br />
* [[download_MicrobeMS|Downloading MicrobeMS]]<br />
* [[computer_specification|Specification of computer configuration]]<br />
* [[install_MicrobeMS|How to install MicrobeMS]]<br />
* [[Screenshot_of_MicrobeMS|Screenshot]] of the main gui<br />
* [[MicrobeMS_Wiki:General_disclaimer |License conditions]]<br />
* [[How_to_Obtain_a_License|How to obtain a license key]]<br />
* [[Mass Spectrometry Databases|Mass spectrometry databases]]<br />
* [[Publications_with_MicrobeMS|Publications with MicrobeMS, acknowledgements]]<br />
* [[Other MALDI-ToF MS Ressources|Other MALDI-ToF MS ressources]]<br />
* [[Frequently_Asked_Questions_(FAQ)|Frequently asked questions (FAQ)]]<br />
<br />
== Management of Metadata Information ==<br />
<br />
* [[Adding / Editing Metadata of MALDI-TOF Mass Spectral Data|Adding / editing metadata of MS data files]] (spectrum metadata, taxonomic information, culture conditions, sample preparation methods, etc.)<br />
<br />
== Description of Data File Formats Specific to MicrobeMS ==<br />
* [[Data_Format_of_Spectral_Multifiles|Description of the format of spectral multifiles (*.muf)]]<br />
* [[Data_Format_of_Peak_List_Files|Description of the format of peak list files (*.pkf)]]<br />
* Description of the format of quality test files (*.mat)<br />
<!-- commented out * [[Format_of_Quality_Test_Result_Files|Description of the format of quality test files (*.mat)]] --><br />
* [[Description of MicrobeMS' main parameter file 'microbems.opt'|Description of the parameter file ''microbems.opt'']]<br />
<br />
== Import and Export of Mass Spectra and Mass Spectral Libraries ==<br />
<br />
* [[Load spectra (Bruker format)|Load spectral data files]] acquired by Bruker Daltonics MALDI-ToF mass spectrometers<br />
* [[Data_Format_of_Spectral_Multifiles|Load / store spectral multifiles (*.muf)]]<br />
* [[Data_Format_of_Peak_List_Files|Load / store peak list files (*.pkf)]]<br />
* [[Store spectra (Bruker format)|Store spectra in a Bruker-specific data format]]<br />
* [[Export spectra to ASCII|Store spectra in a standard ASCII data format]] (export to ASCII)<br />
* [[Store spectra (NeuroDeveloper format)|Store peaklist data in a format specific to the NeuroDeveloper software]] (export to NeuroDeveloper)<br />
* [[Import Mass Spectra in a mzXML Data Format|Import mass spectral data from mzXML data]] (allows importing spectra from Shimadzu/bioMérieux systems)<br />
* [[Export XML Data|Export XML Data]] (required for identification analysis with MicrobeNet from the CDC)<br />
<br />
== Spectral Analysis and Visualization ==<br />
* [[Spectral Pre-processing|Spectral pre-processing]]: smoothing, baseline correction, normalization, cut, auto-calibration, reduce resolution (binning)<br />
* [[MALDI Quality Tests|Quality tests of MALDI-ToF mass spectra]]<br />
* [[Peak Detection|Peak detection]]<br />
* [[Averaging Mass Spectra|Averaging mass spectra]]<br />
* [[Display MS Metadata|Display spectral metadata]]<br />
* [[The Log-File (logfile.txt)|The log-file]] (logfile.txt)<br />
<br />
== Identification and Classification ==<br />
<br />
* [[Unsupervised Hierarchical Cluster Analysis|Unsupervised hierarchical cluster analysis]] <br />
* [[Create database spectra|Creating database spectra from individual microbial mass spectra]]<br />
* Compiling mass spectral databases<br />
* [[Microbial Identification based on Mass Spectral Libraries and Interspectral Distances|Microbial identification based on mass spectral libraries and interspectral distances]]<br />
<!--<br />
* [[Identification Analysis by Neural Networks|Identification analysis by artificial neural networks (ANN,]] requires the NeuroDeveloper software package from [http://www.synthon-analytics.de: Synthon Analytics]) --><br />
* Identification Analysis by Neural Networks, requires the NeuroDeveloper software package from [http://www.synthon-analytics.de: Synthon Analytics])<br />
* [[Identification Analysis by Means of LC-MS&sup1; and ''in silico'' Databases|Identification analysis by means of LC-MS&sup1; and ''in silico'' databases]]<br />
<br />
== Identification of MS Biomarker Peaks ==<br />
<br />
* Generation of [[Creating Pseudo-Gel Views|''pseudo-gel'' views]] from microbial mass spectra<br />
* [[Class Assignment|How to perform class assignments]]<br />
* [[Peak Frequency Test|Peak frequency tests]]<br />
* [[Two-samples t-Tests|Two-samples t-tests]]<br />
* [[Wilcoxon Rank-Sum Tests|Wilcoxon rank-sum tests]]</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1209Two-samples t-Tests2026-05-01T15:30:17Z<p>Laschp: /* Output of the univariate t-test series */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs consecutively two-sample t-tests in segments of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of labeled MALDI-ToF mass spectra that exhibit certain degree of similarity. A two-sample t-test in a given m/z segment returns a test decision for the null hypothesis <math forcemathmode="png">H_{(0)}</math> that the peak intensity data in classes I and II arise from independent random samples from normal distributions with equal means and variances. The alternative hypothesis <math forcemathmode="png">H_{(1)}</math> is that the peak intensity data come from populations with unequal means.<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test t-test] (Wikipedia)<br />
<br />
== Parameter of two-samples t-tests ==<br />
<br />
* '''m/z range''': lower and upper bounds of the m/z region in which the series of t-tests are to be performed<br />
* '''&alpha;''': significance level of the t-tests<br />
* '''''dx''''' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th<br />
* '''use intensities''': defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs<br />
* '''show histogram''': shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' &rarr; ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests. In this example, the m/z segment centered around 2518.0283 Th shows the greatest potential for distinguishing between classes I and II.]]<br />
|[[File:T-test-plot.jpg|400px|thumb|Plot of p-values (log scaled) obtained by univariate t-tests using peak data from individual m/z segments as inputs: The smaller the p-value, the higher the discriminative potential of biomarker peaks at the specific m/z positions]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1208Two-samples t-Tests2026-05-01T15:28:43Z<p>Laschp: /* Output of the univariate t-test series */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs consecutively two-sample t-tests in segments of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of labeled MALDI-ToF mass spectra that exhibit certain degree of similarity. A two-sample t-test in a given m/z segment returns a test decision for the null hypothesis <math forcemathmode="png">H_{(0)}</math> that the peak intensity data in classes I and II arise from independent random samples from normal distributions with equal means and variances. The alternative hypothesis <math forcemathmode="png">H_{(1)}</math> is that the peak intensity data come from populations with unequal means.<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test t-test] (Wikipedia)<br />
<br />
== Parameter of two-samples t-tests ==<br />
<br />
* '''m/z range''': lower and upper bounds of the m/z region in which the series of t-tests are to be performed<br />
* '''&alpha;''': significance level of the t-tests<br />
* '''''dx''''' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th<br />
* '''use intensities''': defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs<br />
* '''show histogram''': shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' &rarr; ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests. In the given example, the m/z segment centered around 2518.0283 Th has the highest potential to discriminate between classes I and II.]]<br />
|[[File:T-test-plot.jpg|400px|thumb|Plot of p-values (log scaled) obtained by univariate t-tests using peak data from individual m/z segments as inputs: The smaller the p-value, the higher the discriminative potential of biomarker peaks at the specific m/z positions]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1207Two-samples t-Tests2026-05-01T15:26:37Z<p>Laschp: /* Output of the univariate t-test series */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs consecutively two-sample t-tests in segments of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of labeled MALDI-ToF mass spectra that exhibit certain degree of similarity. A two-sample t-test in a given m/z segment returns a test decision for the null hypothesis <math forcemathmode="png">H_{(0)}</math> that the peak intensity data in classes I and II arise from independent random samples from normal distributions with equal means and variances. The alternative hypothesis <math forcemathmode="png">H_{(1)}</math> is that the peak intensity data come from populations with unequal means.<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test t-test] (Wikipedia)<br />
<br />
== Parameter of two-samples t-tests ==<br />
<br />
* '''m/z range''': lower and upper bounds of the m/z region in which the series of t-tests are to be performed<br />
* '''&alpha;''': significance level of the t-tests<br />
* '''''dx''''' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th<br />
* '''use intensities''': defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs<br />
* '''show histogram''': shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' &rarr; ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests. In the given example, the m/z segment centered around 2518.0283 Th has the highest potential to discriminate classes I and II.]]<br />
|[[File:T-test-plot.jpg|400px|thumb|Plot of p-values (log scaled) obtained by univariate t-tests using peak data from individual m/z segments as inputs: The smaller the p-value, the higher the discriminative potential of biomarker peaks at the specific m/z positions]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1206Two-samples t-Tests2026-05-01T15:20:10Z<p>Laschp: /* Parameter of two-samples t-tests */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs consecutively two-sample t-tests in segments of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of labeled MALDI-ToF mass spectra that exhibit certain degree of similarity. A two-sample t-test in a given m/z segment returns a test decision for the null hypothesis <math forcemathmode="png">H_{(0)}</math> that the peak intensity data in classes I and II arise from independent random samples from normal distributions with equal means and variances. The alternative hypothesis <math forcemathmode="png">H_{(1)}</math> is that the peak intensity data come from populations with unequal means.<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test t-test] (Wikipedia)<br />
<br />
== Parameter of two-samples t-tests ==<br />
<br />
* '''m/z range''': lower and upper bounds of the m/z region in which the series of t-tests are to be performed<br />
* '''&alpha;''': significance level of the t-tests<br />
* '''''dx''''' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th<br />
* '''use intensities''': defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs<br />
* '''show histogram''': shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' &rarr; ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests]]<br />
|[[File:T-test-plot.jpg|400px|thumb|Plot of p-values (log scaled) obtained by univariate t-tests using peak data from individual m/z segments as inputs: The smaller the p-value, the higher the discriminative potential of biomarker peaks at the specific m/z positions]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1202Two-samples t-Tests2026-05-01T15:13:39Z<p>Laschp: /* Output of the univariate t-test series */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs consecutively two-sample t-tests in segments of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of labeled MALDI-ToF mass spectra that exhibit certain degree of similarity. A two-sample t-test in a given m/z segment returns a test decision for the null hypothesis <math forcemathmode="png">H_{(0)}</math> that the peak intensity data in classes I and II arise from independent random samples from normal distributions with equal means and variances. The alternative hypothesis <math forcemathmode="png">H_{(1)}</math> is that the peak intensity data come from populations with unequal means.<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test t-test] (Wikipedia)<br />
<br />
== Parameter of two-samples t-tests ==<br />
<br />
* m/z range: lower and upper bounds of the m/z region in which the series of t-tests are to be performed<br />
* &alpha;: significance level of the t-tests<br />
* ''dx'' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th<br />
* intensity: defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs<br />
* show histogram: shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' &rarr; ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests]]<br />
|[[File:T-test-plot.jpg|400px|thumb|Plot of p-values (log scaled) obtained by univariate t-tests using peak data from individual m/z segments as inputs: The smaller the p-value, the higher the discriminative potential of biomarker peaks at the specific m/z positions]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1201Two-samples t-Tests2026-05-01T14:58:19Z<p>Laschp: /* Introduction */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs consecutively two-sample t-tests in segments of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of labeled MALDI-ToF mass spectra that exhibit certain degree of similarity. A two-sample t-test in a given m/z segment returns a test decision for the null hypothesis <math forcemathmode="png">H_{(0)}</math> that the peak intensity data in classes I and II arise from independent random samples from normal distributions with equal means and variances. The alternative hypothesis <math forcemathmode="png">H_{(1)}</math> is that the peak intensity data come from populations with unequal means.<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test t-test] (Wikipedia)<br />
<br />
== Parameter of two-samples t-tests ==<br />
<br />
* m/z range: lower and upper bounds of the m/z region in which the series of t-tests are to be performed<br />
* &alpha;: significance level of the t-tests<br />
* ''dx'' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th<br />
* intensity: defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs<br />
* show histogram: shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' &rarr; ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests]]<br />
|[[File:T-test-plot.jpg|400px|thumb|p-values plot of univariate t-tests (log scaled): The smaller the p-value at the specific m/z position the higher the discriminative potential of biomarker peaks at this position]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1200Two-samples t-Tests2026-05-01T14:56:51Z<p>Laschp: /* Introduction */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs consecutively two-samples t-tests in segments of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of labeled MALDI-ToF mass spectra that exhibit certain degree of similarity. A two-samples t-test in a given m/z segment returns a test decision for the null hypothesis <math forcemathmode="png">H_{(0)}</math> that the peak intensity data in classes I and II arise from independent random samples from normal distributions with equal means and variances. The alternative hypothesis <math forcemathmode="png">H_{(1)}</math> is that the peak intensity data come from populations with unequal means.<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test t-test] (Wikipedia)<br />
<br />
== Parameter of two-samples t-tests ==<br />
<br />
* m/z range: lower and upper bounds of the m/z region in which the series of t-tests are to be performed<br />
* &alpha;: significance level of the t-tests<br />
* ''dx'' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th<br />
* intensity: defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs<br />
* show histogram: shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' &rarr; ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests]]<br />
|[[File:T-test-plot.jpg|400px|thumb|p-values plot of univariate t-tests (log scaled): The smaller the p-value at the specific m/z position the higher the discriminative potential of biomarker peaks at this position]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1199Two-samples t-Tests2026-05-01T14:56:22Z<p>Laschp: /* Introduction */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs consecutively two-samples t-tests in segments of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of labeled MALDI-ToF mass spectra that exhibit certain degree of similarity. A two-samples t-test in a given m/z segment returns a test decision for the null hypothesis <math forcemathmode="png">H_{(0)}</math> that the peak intensity data in classes I and II arise from independent random samples from normal distributions with equal means and variances. The alternative hypothesis <math forcemathmode="png">H_{(1)}</math> is that the peak intensity data come from populations with unequal means.<br />
<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test t-test] (Wikipedia)<br />
<br />
== Parameter of two-samples t-tests ==<br />
<br />
* m/z range: lower and upper bounds of the m/z region in which the series of t-tests are to be performed<br />
* &alpha;: significance level of the t-tests<br />
* ''dx'' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th<br />
* intensity: defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs<br />
* show histogram: shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' &rarr; ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests]]<br />
|[[File:T-test-plot.jpg|400px|thumb|p-values plot of univariate t-tests (log scaled): The smaller the p-value at the specific m/z position the higher the discriminative potential of biomarker peaks at this position]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1198Two-samples t-Tests2026-05-01T14:55:39Z<p>Laschp: /* Introduction */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs consecutively two-samples t-tests in segments of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of labeled MALDI-ToF mass spectra that exhibit certain degree of similarity. A two-samples t-test in a given m/z segment returns a test decision for the null hypothesis <math forcemathmode="png">H_{(0)}</math> that the peak intensity data in classes I and class II arise from independent random samples from normal distributions with equal means and variances. The alternative hypothesis H(1) is that the peak intensity data come from populations with unequal means.<br />
<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test t-test] (Wikipedia)<br />
<br />
== Parameter of two-samples t-tests ==<br />
<br />
* m/z range: lower and upper bounds of the m/z region in which the series of t-tests are to be performed<br />
* &alpha;: significance level of the t-tests<br />
* ''dx'' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th<br />
* intensity: defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs<br />
* show histogram: shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' &rarr; ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests]]<br />
|[[File:T-test-plot.jpg|400px|thumb|p-values plot of univariate t-tests (log scaled): The smaller the p-value at the specific m/z position the higher the discriminative potential of biomarker peaks at this position]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1197Two-samples t-Tests2026-05-01T14:50:26Z<p>Laschp: /* Parameter of two-samples t-tests */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs two-samples t-tests in each segment of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of mass spectra exhibiting certain degree of similarity. A two-samples t-test in a given m/z segment returns a test decision for the null hypothesis H(0) that the peak intensity data in class I and class II come from independent random samples from normal distributions with equal means and variances. The alternative hypothesis H(1) is that the peak intensity data come from populations with unequal means.<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test t-test] (Wikipedia)<br />
<br />
== Parameter of two-samples t-tests ==<br />
<br />
* m/z range: lower and upper bounds of the m/z region in which the series of t-tests are to be performed<br />
* &alpha;: significance level of the t-tests<br />
* ''dx'' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th<br />
* intensity: defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs<br />
* show histogram: shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' &rarr; ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests]]<br />
|[[File:T-test-plot.jpg|400px|thumb|p-values plot of univariate t-tests (log scaled): The smaller the p-value at the specific m/z position the higher the discriminative potential of biomarker peaks at this position]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1194Two-samples t-Tests2026-05-01T13:45:40Z<p>Laschp: /* Introduction */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs two-samples t-tests in each segment of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of mass spectra exhibiting certain degree of similarity. A two-samples t-test in a given m/z segment returns a test decision for the null hypothesis H(0) that the peak intensity data in class I and class II come from independent random samples from normal distributions with equal means and variances. The alternative hypothesis H(1) is that the peak intensity data come from populations with unequal means.<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test t-test] (Wikipedia)<br />
<br />
== Parameter of two-samples t-tests ==<br />
<br />
* m/z range: lower and upper bounds of the m/z region in which the t-tests are to be performed<br />
* &alpha;: significance level of the t-tests<br />
* ''dx'' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th<br />
* intensity: defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs<br />
* show histogram: shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' &rarr; ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests]]<br />
|[[File:T-test-plot.jpg|400px|thumb|p-values plot of univariate t-tests (log scaled): The smaller the p-value at the specific m/z position the higher the discriminative potential of biomarker peaks at this position]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1193Two-samples t-Tests2026-05-01T13:45:16Z<p>Laschp: /* Introduction */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs two-samples t-tests in each segment of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of mass spectra exhibiting certain degree of similarity. A two-samples t-test in a given m/z segment returns a test decision for the null hypothesis H(0) that the peak intensity data in class I and class II come from independent random samples from normal distributions with equal means and variances. The alternative hypothesis H(1) is that the peak intensity data come from populations with unequal means.<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test | t-test] (Wikipedia)<br />
<br />
== Parameter of two-samples t-tests ==<br />
<br />
* m/z range: lower and upper bounds of the m/z region in which the t-tests are to be performed<br />
* &alpha;: significance level of the t-tests<br />
* ''dx'' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th<br />
* intensity: defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs<br />
* show histogram: shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' &rarr; ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests]]<br />
|[[File:T-test-plot.jpg|400px|thumb|p-values plot of univariate t-tests (log scaled): The smaller the p-value at the specific m/z position the higher the discriminative potential of biomarker peaks at this position]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1191Two-samples t-Tests2026-05-01T13:44:18Z<p>Laschp: /* Parameter of the two-samples t-test */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs two-samples t-tests in each segment of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of mass spectra exhibiting certain degree of similarity. A two-samples t-test in a given m/z segment returns a test decision for the null hypothesis H(0) that the peak intensity data in class I and class II come from independent random samples from normal distributions with equal means and variances. The alternative hypothesis H(1) is that the peak intensity data come from populations with unequal means.<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test| t-test] (Wikipedia)<br />
<br />
== Parameter of two-samples t-tests ==<br />
<br />
* m/z range: lower and upper bounds of the m/z region in which the t-tests are to be performed<br />
* &alpha;: significance level of the t-tests<br />
* ''dx'' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th<br />
* intensity: defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs<br />
* show histogram: shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' &rarr; ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests]]<br />
|[[File:T-test-plot.jpg|400px|thumb|p-values plot of univariate t-tests (log scaled): The smaller the p-value at the specific m/z position the higher the discriminative potential of biomarker peaks at this position]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1190Two-samples t-Tests2026-05-01T13:43:42Z<p>Laschp: /* Performing t-test series */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs two-samples t-tests in each segment of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of mass spectra exhibiting certain degree of similarity. A two-samples t-test in a given m/z segment returns a test decision for the null hypothesis H(0) that the peak intensity data in class I and class II come from independent random samples from normal distributions with equal means and variances. The alternative hypothesis H(1) is that the peak intensity data come from populations with unequal means.<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test| t-test] (Wikipedia)<br />
<br />
== Parameter of the two-samples t-test ==<br />
<br />
* m/z range: lower and upper bounds of the m/z region in which the t-tests are to be performed<br />
* &alpha;: significance level of the t-tests<br />
* ''dx'' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th<br />
* intensity: defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs<br />
* show histogram: shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' &rarr; ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests]]<br />
|[[File:T-test-plot.jpg|400px|thumb|p-values plot of univariate t-tests (log scaled): The smaller the p-value at the specific m/z position the higher the discriminative potential of biomarker peaks at this position]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1188Two-samples t-Tests2026-05-01T13:42:14Z<p>Laschp: /* Parameter of the two-samples t-test */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs two-samples t-tests in each segment of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of mass spectra exhibiting certain degree of similarity. A two-samples t-test in a given m/z segment returns a test decision for the null hypothesis H(0) that the peak intensity data in class I and class II come from independent random samples from normal distributions with equal means and variances. The alternative hypothesis H(1) is that the peak intensity data come from populations with unequal means.<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test| t-test] (Wikipedia)<br />
<br />
== Parameter of the two-samples t-test ==<br />
<br />
* m/z range: lower and upper bounds of the m/z region in which the t-tests are to be performed<br />
* &alpha;: significance level of the t-tests<br />
* ''dx'' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th<br />
* intensity: defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs<br />
* show histogram: shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' --> ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests]]<br />
|[[File:T-test-plot.jpg|400px|thumb|p-values plot of univariate t-tests (log scaled): The smaller the p-value at the specific m/z position the higher the discriminative potential of biomarker peaks at this position]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1185Two-samples t-Tests2026-05-01T13:40:39Z<p>Laschp: /* Parameter of the two-samples t-test */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs two-samples t-tests in each segment of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of mass spectra exhibiting certain degree of similarity. A two-samples t-test in a given m/z segment returns a test decision for the null hypothesis H(0) that the peak intensity data in class I and class II come from independent random samples from normal distributions with equal means and variances. The alternative hypothesis H(1) is that the peak intensity data come from populations with unequal means.<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test| t-test] (Wikipedia)<br />
<br />
== Parameter of the two-samples t-test ==<br />
<br />
* m/z range: lower and upper bounds of the m/z region in which the t-tests are to be performed<br />
* &alpha;: significance level of the t-tests<br />
* ''dx'' (ppm): a parameter defining the relative width and thus the number of the spectrum segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th. <br />
* intensity: defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs.<br />
* show histogram: shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables.<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' --> ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests]]<br />
|[[File:T-test-plot.jpg|400px|thumb|p-values plot of univariate t-tests (log scaled): The smaller the p-value at the specific m/z position the higher the discriminative potential of biomarker peaks at this position]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Two-samples_t-Tests&diff=1184Two-samples t-Tests2026-05-01T13:39:46Z<p>Laschp: /* Parameter of the two-samples t-test */</p>
<hr />
<div>__FORCETOC__<br />
== Introduction ==<br />
<br />
[[File:T-test.jpg|right|thumb|Input parameters for univariate t-tests]]<br />
<br />
This function performs two-samples t-tests in each segment of the MALDI-ToF mass spectra using peak table data as inputs. t-tests are useful for biomarker screening in ensembles of mass spectra exhibiting certain degree of similarity. A two-samples t-test in a given m/z segment returns a test decision for the null hypothesis H(0) that the peak intensity data in class I and class II come from independent random samples from normal distributions with equal means and variances. The alternative hypothesis H(1) is that the peak intensity data come from populations with unequal means.<br />
<br />
See also [https://en.wikipedia.org/wiki/Student's_t-test| t-test] (Wikipedia)<br />
<br />
== Parameter of the two-samples t-test ==<br />
<br />
* m/z range: lower and upper bounds of the m/z region in which the t-tests are to be performed<br />
* &alpha;: significance level of the t-tests<br />
* ''dx'' (ppm): a parameter defining the relative width and thus the number of the m/z spectra segments. A spectrum segment centered at position <math forcemathmode="png">{x_{i}}</math> covers a m/z interval of an absolute width equaling <math forcemathmode="png">width_{abs,x(i)} = {x_{i}*dx*10^{-6}}</math>. The lower and upper bounds of the spectrum segments are defined by <math forcemathmode="png">[{x_{i}*(1-dx)*0.5*10^{-6}}]</math> (lower bound) and <math forcemathmode="png">[{x_{i}*(1+dx)*0.5*10^{-6}}]</math> (upper bound), respectively. Consequently, a spectrum segment of width ''dx''=1000 and centered at <math forcemathmode="png">{x_{i}}</math>=2000 Th would be 2 Th wide with boundaries located at 1999 and 2001 Th. <br />
* intensity: defines if barcode spectra (checkbox unchecked) or peak weighting factors (checked) are utilized as test inputs.<br />
* show histogram: shows a histogram with test outputs (p-values, AUC, etc.) and provides also the mean, median and the standard deviation of the test variables.<br />
<br />
== Performing t-test series ==<br />
<br />
1. Load the mass spectral data files via the [[Load spectra (Bruker format)|load spectra]] (Bruker data file format), [[Import Mass Spectra in a mzXML Data Format|import spectra from mzXML data]], or the ''load MS multifile'' options of the ''File'' pull down menu.<br />
<br />
2. Two-samples t-tests are carried out from labeled spectra, i.e. from spectra with a [[Class Assignment|class assignment]]. To perform the test label two groups of spectra as class 1 and as class 2, respectively. Labeling, or class assignment, can be carried out by selecting the appropriate spectra and choosing ''class assignments'' --> ''class X'' from the ''Edit'' pull down menu.<br />
<br />
3. The t-test routine always starts from original MALDI-ToF mass spectra, i.e. [[Spectral Pre-processing| spectral pre-processing]] and [[Peak Detection|peak detection]] is carried out automatically using pre-defined parameters. Existing pre-processed spectra and pre-defined peak tables are ignored by the test routine.<br />
<br />
4. Define test parameter, such as &alpha; (significance level), the m/z range and dx (''ppm'') which has a default value of 1000 (relative, in ppm). The parameter dx defines the width of m/z segments in which spectra are divided during the test. Peaks found in the same m/z segment are considered identical while mass peaks in different segments are considered different peaks. <br />
<br />
5. When finished select ''t-test'' from the ''Analysis'' pull down menu. Choose options ''plot decision for H(0)'', ''plot p-values'' or ''plot t-values'', to obtain the respective outputs of the t-tests.<br />
<br />
== Output of the univariate t-test series ==<br />
<br><br />
Example of the output from a serial t-test taken from the [[The Log-File (logfile.txt)|log file]] of MicrobeMS:<br />
<br />
{|<br />
|- style="vertical-align:top;"<br />
|[[File:t-test-cmdln-output.png|474px|thumb|Command line output of t-tests]]<br />
|[[File:T-test-plot.jpg|400px|thumb|p-values plot of univariate t-tests (log scaled): The smaller the p-value at the specific m/z position the higher the discriminative potential of biomarker peaks at this position]]<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Download_MicrobeMS&diff=1156Download MicrobeMS2026-05-01T10:53:06Z<p>Laschp: /* MicrobeMS stand-alone (Windows) */</p>
<hr />
<div>__TOC__<br />
<br />
MicrobeMS is available in two different editions: in (i) a stand-alone Windows 64-bit version requiring the Matlab Compiler Runtime (MCR) 64-bit and (ii) a Matlab pcode toolbox version requiring Matlab R2014 (Windows / Linux) or later.<br />
Please note that you accept with downloading the [[MicrobeMS_Wiki:General_disclaimer | license conditions]] of MicrobeMS.<br />
<br />
=== MicrobeMS stand-alone (Windows) ===<br />
<br />
<font color="red">'''NEW'''</font> - Microbe MS 0.93 stand-alone 64-bit version (Windows, May 2026). This version requires Matlab's MCR 2023b (64-bit, Windows). Please use the following link to download the installer for this edition of MicrobeMS<br />
<br />
[https://wiki.microbe-ms.com/uploads/microbems.v.093.R2023b.setup.zip: '''microbems.v.093.R2023b.setup.zip''']<br />
<br />
Microbe MS 0.92 stand-alone 64-bit version (Windows, January 2026). This version requires Matlab's MCR 2023b (64-bit, Windows).<br />
<br />
[https://wiki.microbe-ms.com/uploads/microbems.v.092.R2023b.setup.zip: '''microbems.v.092.R2023b.setup.zip''']<br />
<br />
Microbe MS 0.90d stand-alone 64-bit version (Windows, July 2025), requires Matlab's MCR 2014a (64-bit, Windows).<br />
<br />
[https://wiki.microbe-ms.com/uploads/microbems.v.090d.R2023b.setup.zip: '''microbems.v.090d.R2023b.setup.zip''']<br />
<br />
Microbe MS 0.89 stand-alone 64-bit version (Windows, February 2025), requires Matlab's MCR 2014a (64-bit, Windows).<br />
<br />
[https://wiki.microbe-ms.com/uploads/microbems.v.089.R2014a.setup.zip: '''microbems.v.089.R2014a.setup.zip''']<br />
<br />
Microbe MS 0.84 stand-alone 64-bit version (Windows) from February 2022, requires Matlab's MCR 2014a.: <br />
<br />
[https://wiki.microbe-ms.com/uploads/microbems.v.084.setup.zip: '''microbems.v.084.setup.zip''']<br />
<br />
=== MicrobeMS pcode (Windows and Linux) ===<br />
<br />
<font color="red">'''NEW'''</font> - MicrobeMS version 0.92 Matlab pcode for Windows and Linux (January 2026):<br />
requires Matlab R2022a or newer<br />
<br />
[https://wiki.microbe-ms.com/uploads/pcode-microbems-v092.zip: '''pcode-microbems-v092.zip''']<br />
<br />
MicrobeMS version 0.87 Matlab pcode for Windows and Linux (June 2024):<br />
requires Matlab R2022a or newer<br />
<br />
[https://wiki.microbe-ms.com/uploads/pcode-microbems-v087.zip: '''pcode-microbems-v087.zip''']<br />
<br />
MicrobeMS version 0.82 Matlab pcode for Windows and Linux (December 2019):<br />
<br />
[https://wiki.microbe-ms.com/uploads/pcode-microbems-v082.zip: '''pcode-microbems-v082.zip''']<br />
<br />
=== Test Spectra and Databases ===<br />
<br />
MALDI-ToF mass spectra from the ''so called'' [https://pubmed.ncbi.nlm.nih.gov/26063856/ '''RKI ring trial study'''] (zip archive, Bruker Daltonics MS data format):<br />
<br />
[https://wiki.microbe-ms.com/uploads/ring-trial-RKI-spectra.zip '''ring-trial-RKI-spectra.zip''']<br />
<br />
MALDI-ToF mass spectra from the ''so called'' [https://pubmed.ncbi.nlm.nih.gov/26063856/ '''RKI ring trial study'''] (Matlab data format, structure array ''spec''), <br><br />
see also [[Data_Format_of_Spectral_Multifiles|Format of spectra multifiles (*.muf)]]:<br />
<br />
[https://wiki.microbe-ms.com/uploads/RKI-ring-trial-spectra.muf: '''RKI-ring-trial-spectra.muf''']<br />
<br />
Peak list files obtained from mass spectra of strains of the ''so called'' [https://pubmed.ncbi.nlm.nih.gov/26063856/ '''RKI ring trial study'''] (Matlab data format, structure array ''C''),<br><br />
see also [[Data_Format_of_Peak_List_Files|Format of peaks list files (*.pkf)]] to obtain information on the file format<br />
<br />
[https://wiki.microbe-ms.com/uploads/RKI-ring-trial-test-data.pkf: '''RKI-ring-trial-test-data.pkf''']<br />
<br />
MS Excel template required to define and transfer metadata items into MicrobeMS,<br><br />
for file format information see [[Adding / Editing Metadata of MALDI-TOF Mass Spectral Data|Adding / editing metadata of MS data files]]:<br />
<br />
[https://wiki.microbe-ms.com/uploads/MALDI-Fields.xls: '''MALDI-Fields.xls''']<br />
<br />
Download the most actual database versions with microbial MALDI-ToF MS, or synthetic LC-MS libraries:<br />
<br />
[[Mass_Spectrometry_Databases |Mass Spectrometry Databases from the RKI at ZENODO]]</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Download_MicrobeMS&diff=1155Download MicrobeMS2026-05-01T10:52:17Z<p>Laschp: /* MicrobeMS stand-alone (Windows) */</p>
<hr />
<div>__TOC__<br />
<br />
MicrobeMS is available in two different editions: in (i) a stand-alone Windows 64-bit version requiring the Matlab Compiler Runtime (MCR) 64-bit and (ii) a Matlab pcode toolbox version requiring Matlab R2014 (Windows / Linux) or later.<br />
Please note that you accept with downloading the [[MicrobeMS_Wiki:General_disclaimer | license conditions]] of MicrobeMS.<br />
<br />
=== MicrobeMS stand-alone (Windows) ===<br />
<br />
<font color="red">'''NEW'''</font> - Microbe MS 0.93 stand-alone 64-bit version (Windows, May 2026). This version requires Matlab's MCR 2023b (64-bit, Windows). Please use the following link to download the installer for this edition of MicrobeMS<br />
<br />
Microbe MS 0.92 stand-alone 64-bit version (Windows, January 2026). This version requires Matlab's MCR 2023b (64-bit, Windows).<br />
<br />
[https://wiki.microbe-ms.com/uploads/microbems.v.092.R2023b.setup.zip: '''microbems.v.092.R2023b.setup.zip''']<br />
<br />
Microbe MS 0.90d stand-alone 64-bit version (Windows, July 2025), requires Matlab's MCR 2014a (64-bit, Windows).<br />
<br />
[https://wiki.microbe-ms.com/uploads/microbems.v.090d.R2023b.setup.zip: '''microbems.v.090d.R2023b.setup.zip''']<br />
<br />
Microbe MS 0.89 stand-alone 64-bit version (Windows, February 2025), requires Matlab's MCR 2014a (64-bit, Windows).<br />
<br />
[https://wiki.microbe-ms.com/uploads/microbems.v.089.R2014a.setup.zip: '''microbems.v.089.R2014a.setup.zip''']<br />
<br />
Microbe MS 0.84 stand-alone 64-bit version (Windows) from February 2022, requires Matlab's MCR 2014a.: <br />
<br />
[https://wiki.microbe-ms.com/uploads/microbems.v.084.setup.zip: '''microbems.v.084.setup.zip''']<br />
<br />
=== MicrobeMS pcode (Windows and Linux) ===<br />
<br />
<font color="red">'''NEW'''</font> - MicrobeMS version 0.92 Matlab pcode for Windows and Linux (January 2026):<br />
requires Matlab R2022a or newer<br />
<br />
[https://wiki.microbe-ms.com/uploads/pcode-microbems-v092.zip: '''pcode-microbems-v092.zip''']<br />
<br />
MicrobeMS version 0.87 Matlab pcode for Windows and Linux (June 2024):<br />
requires Matlab R2022a or newer<br />
<br />
[https://wiki.microbe-ms.com/uploads/pcode-microbems-v087.zip: '''pcode-microbems-v087.zip''']<br />
<br />
MicrobeMS version 0.82 Matlab pcode for Windows and Linux (December 2019):<br />
<br />
[https://wiki.microbe-ms.com/uploads/pcode-microbems-v082.zip: '''pcode-microbems-v082.zip''']<br />
<br />
=== Test Spectra and Databases ===<br />
<br />
MALDI-ToF mass spectra from the ''so called'' [https://pubmed.ncbi.nlm.nih.gov/26063856/ '''RKI ring trial study'''] (zip archive, Bruker Daltonics MS data format):<br />
<br />
[https://wiki.microbe-ms.com/uploads/ring-trial-RKI-spectra.zip '''ring-trial-RKI-spectra.zip''']<br />
<br />
MALDI-ToF mass spectra from the ''so called'' [https://pubmed.ncbi.nlm.nih.gov/26063856/ '''RKI ring trial study'''] (Matlab data format, structure array ''spec''), <br><br />
see also [[Data_Format_of_Spectral_Multifiles|Format of spectra multifiles (*.muf)]]:<br />
<br />
[https://wiki.microbe-ms.com/uploads/RKI-ring-trial-spectra.muf: '''RKI-ring-trial-spectra.muf''']<br />
<br />
Peak list files obtained from mass spectra of strains of the ''so called'' [https://pubmed.ncbi.nlm.nih.gov/26063856/ '''RKI ring trial study'''] (Matlab data format, structure array ''C''),<br><br />
see also [[Data_Format_of_Peak_List_Files|Format of peaks list files (*.pkf)]] to obtain information on the file format<br />
<br />
[https://wiki.microbe-ms.com/uploads/RKI-ring-trial-test-data.pkf: '''RKI-ring-trial-test-data.pkf''']<br />
<br />
MS Excel template required to define and transfer metadata items into MicrobeMS,<br><br />
for file format information see [[Adding / Editing Metadata of MALDI-TOF Mass Spectral Data|Adding / editing metadata of MS data files]]:<br />
<br />
[https://wiki.microbe-ms.com/uploads/MALDI-Fields.xls: '''MALDI-Fields.xls''']<br />
<br />
Download the most actual database versions with microbial MALDI-ToF MS, or synthetic LC-MS libraries:<br />
<br />
[[Mass_Spectrometry_Databases |Mass Spectrometry Databases from the RKI at ZENODO]]</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Frequently_Asked_Questions_(FAQ)&diff=1154Frequently Asked Questions (FAQ)2026-05-01T10:02:26Z<p>Laschp: /* What is the most actual version of MicrobeMS? */</p>
<hr />
<div>== What is MicrobeMS? ==<br />
<br />
The MicrobeMS software package is a program initially designed for the analysis of MALDI-ToF mass spectra of microbial samples. The MicrobeMS software was developed by Peter Lasch at the [http://www.rki.de/EN/Home/homepage_node.html: Robert-Koch-Institute (RKI)] in Berlin, Germany, and can be used to identify microbial strains and species based on their mass spectral patterns (MALDI-ToF MS and LC-MS).<br />
<br />
== What is the most actual version of MicrobeMS? ==<br />
<br />
The most actual version of the MicrobeMS software is MicrobeMS v. 0.93 from May 2026. The MicrobeMS software is continuously being developed further and can be downloaded [[download_MicrobeMS|here]].<br />
<br />
'''May. 2026''': MicrobeMS v.0.93 released<br />
<br />
* Minor edits: peak labels, error reporting, functionality of button ''more'' in function ''cmpr'', increased accuracy of peak detection, etc. <br />
* Many code improvements & bug fixes<br />
<br />
'''Jan. 2026''': MicrobeMS v.0.92<br />
<br />
* [[Export XML Data|''XML export filter'']] for exporting MALDI-ToF MS spectrum data in to a format suitable for utilization of the MicrobeNet solution of the CDC's.<br />
* New functionalities of the software function [[Microbial Identification based on Mass Spectral Libraries and Interspectral Distances|''Microbial identification based on mass spectral libraries and interspectral distances'']]: introducing a MBT like identification method<br />
* [[MALDI Quality Tests|Quality test]] function significantly revised<br />
* Many code improvements & bug fixes<br />
<br />
'''Jun. 2025''': MicrobeMS v.0.90<br />
<br />
* Major revisions of the function [[Unsupervised Hierarchical Cluster Analysis|''Unsupervised hierarchical cluster analysis'']] <br />
* Code improvements and bug fixes<br />
<br />
'''Feb. 2025''': MicrobeMS v.0.89<br />
<br />
* Spectral prep-processing functions revised, see [https://wiki-ms.microbe-ms.com/index.php?title=Spectral_Pre-processing ''MicrobeMS - Spectral Pre-processing''] for details<br />
* New function [https://wiki-ms.microbe-ms.com/index.php?title=MALDI_Quality_Tests ''Quality tests''] introduced<br />
* Code improvements and bug fixes<br />
<br />
'''Nov. 2019''': New functions and bug fixes of version 0.82:<br />
<br />
* Further optimization of the function ''[[Microbial Identification based on Mass Spectral Libraries and Interspectral Distances|Microbial identification based on mass spectral libraries and interspectral distances]]'': Speed improvement by a factor of ~2 compared with version 0.80.<br />
* MicrobeMS v. 0.82 allows analysis of LC-MS&sup1; spectra from microorganisms. Identification analysis of the LC-MS&sup1; data requires a synthetic ''in silico'' database of peptide mass data calculated from microbial genomes (see see '''Preprint''' Lasch P, Schneider A, Blumenscheit C and Doellinger J, [https://doi.org/10.1101/870089 ''Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS&sup1;) and in silico Peptide Mass Data]'', bioRxiv (Dec 10, '''2018'''), doi:10.1101/870089.)<br />
* Code improvements and bug fixes<br />
<br />
'''Feb. 2017''': New functions and bug fixes of version 0.80 (selection):<br />
<br />
* Re-designed interface to the NeuroDeveloper, a software for spectral analysis by artificial neural networks<br />
* The import filter for binary Bruker Daltonics spectra files has been completely revised. This filter supports now also importing of MS data calibrated with the function ''cubic enhanced''.<br />
* New design of the function ''[[Microbial Identification based on Mass Spectral Libraries and Interspectral Distances|Microbial identification based on mass spectral libraries and interspectral distances]]'': Matlab code for calculation of inter-spectral distances is now fully vectorized => speed improvement by a factor of ~4.<br />
* Enhanced functionality of the option ''vary calibration parameters''<br />
* Many code improvements & bug fixes.<br />
<br />
== Is there a standalone version of MicrobeMS? ==<br />
<br />
Yes, a standalone version of the MicrobeMS toolbox has been available since November 2016. The MicrobeMS standalone runs on Windows 7/8/8.1/10 and 11. Like previous pcode versions, the stand-alone version of MicrobeMS is based on Matlab, so the free Matlab Compiler Runtime environment is required. Please see [[install_MicrobeMS|How to install MicrobeMS]] and [[download_MicrobeMS|Downloading MicrobeMS]] for more details.<br />
<br />
== MicrobeMS for Linux. Can MicrobeMS be used under Linux? ==<br />
<br />
The first Linux version of MicrobeMS has been released in November 2019. This, and later software versions were tested under Matlab / Debian versions 10 and 11 and are available as a Matlab pcode toolboxes, i.e. requires Matlab plus two Matlab toolboxes (Statistics and Bioinformatics Toolboxes). More information can be found [[install_MicrobeMS|here]].<br><br />
Update Oct 2024: A compiled Linux version (0.88) is available on request. Note that this version requires installation of the Matlab Compiler Runtime (MCR) R2020a.<br />
<br />
== What is the Matlab Compiler Runtime (MCR) and why do I need to install it? ==<br />
<br />
MicrobeMS is Matlab-based software. The Matlab component runtime is a standalone set of shared libraries that enables the execution of compiled Matlab applications or components on computers that do not have Matlab installed. The Matlab Compiler Runtime (MCR) is available at no charge from the Mathworks Web site. It is important that the version of MCR that runs the application on the target computer is compatible with the version of the Matlab compiler used (i.e. '''MCR 2014a Windows 64-bit''' must be installed to use version 0.84 of MicrobeMS [v. 0.82]). Later versions can be installed either as compatible with '''MCR 2014a Windows 64-bit''' with ''microbems.v.089.R2014a.setup.zip'' or '''MCR 2023b Windows 64-bit''' using ''microbems.v.089.R2023b.setup.zip''.<br />
<br />
== Why I do need to install the MCR 2014a 64-bit and not a more recent version? ==<br />
<br><br />
''This question has now been resolved, as a version for MCR 2023b is available since March 2025.''<br><br />
<br><br />
First of all, MicrobeMS for Windows has been compiled with the Matlab compiler of Matlab version R2014a (Windows 64-bit). But why was a more recent compiler version not used? <br />
The answer to this question has two parts:<br><br />
First, new Matlab versions usually introduce new features, while existing features may be modified or even removed. These changes require extensive source code compatibility checks when migrating to a newer Matlab / Matlab compiler version. Second, with the R2014b release, The Mathworks introduced major changes to the underlying graphics libraries, see https://de.mathworks.com/help/matlab/graphics_transition/major-graphics-changes-in-r2014b.html for details. I noticed that these changes caused performance problems on some computers, see https://de.mathworks.com/matlabcentral/answers/203918-slow-plotting-performance-starting-from-matlab-r2014b for an example. <br><br />
With this in mind, I decided to wait for the performance problems to be solved by hardware evolution, i.e. to wait for faster hardware to solve the problem by itself.<br />
<br />
== I have installed MicrobeMS, but I would like to use also spectral databases ==<br />
<br />
Databases of microbial mass spectra are not provided with the software (except some test spectra of selected ''Escherichia coli'' strains). For a limited number of users we provide spectral databases from our ''Yersinia'' and ''Bacillus'' study on personal request (signing of a data transfer agreement - DTA - is required). Please send an email with your request to the following address: [mailto:lasch@microbe-ms.com lasch@microbe-ms.com].<br><br />
<br />
'''UPDATE Jan 2026''': An ''in silico'' MALDI-ToF MS database is available (CC-BY-NC-SA license). This database has been derived from UniprotKB proteomics databases, i.e. ultimately from microbial genomes. This database is still highly experimental and should not be used for diagnostic purposes. More details will follow in the near future.<br />
<br />
'''UPDATE May 2023''': MALDI-ToF MS database version 4 is available, again under the Creatives Commons license (CC-BY-NC-SA). The RKI Database v.4 now contains a total of 11055 MALDI-ToF mass spectra from 1599 microbial strains of highly pathogenic (i.e. biosafety level 3, BSL-3) bacteria such as ''Bacillus anthracis'', ''Brucella melitensis'', ''Yersinia pestis'', ''Burkholderia mallei'' / ''pseudomallei'' and ''Francisella tularensis'' as well as a selection of spectra of their close and distant relatives, for details see https://doi.org/10.5281/zenodo.7702375.<br />
<br />
'''UPDATE Dec 2019''': The concept of microbial identification by means of MALDI-ToF mass spectrometry measurements of cultivated microbial cells and comparison with entries of a spectral library has been adapted for LC-MS&sup1; based microbial identification, see '''Preprint''' Lasch P, Schneider A, Blumenscheit C and Doellinger J, [https://doi.org/10.1101/870089 ''Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS&sup1;) and in silico Peptide Mass Data]'', bioRxiv (Dec 10, '''2018'''), doi:10.1101/870089.<br><br />
The respective ''in silico'' database can be downloaded from Zenodo (1.5 GB!): [https://doi.org/10.5281/zenodo.3573996 ''In silico Database for Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS&sup1;)''] Zenodo, December 13, 2019.<br> (cf. also [[Identification Analysis by Means of LC-MS&sup1; and ''in silico'' Databases|Identification analysis by means of LC-MS&sup1; and ''in silico'' databases]]).<br />
<br />
'''UPDATE Nov 2018''': The third update of the RKI MALDI-ToF MS database is available (Creatives Commons license, CC-BY-NC-SA). <br />
The RKI database v.3 contains a total of 6264 mass spectra of highly pathogenic (i.e. biosafety level 3, BSL-3) bacteria such as ''Bacillus anthracis'', ''Yersinia pestis'', ''Burkholderia mallei'', ''Burkholderia pseudomallei'' and ''Francisella tularensis'' as well as a selection of spectra from their close and more distant relatives. The database can be used as a reference for diagnosis of BSL-3 bacteria using proprietary and free software packages for MALDI-ToF MS-based microbial identification. Spectral data are distributed as a 7-zip archive that contains the original mass spectra in the original data format (Bruker Daltonics), see [https://doi.org/10.5281/zenodo.1880975 https://doi.org/10.5281/zenodo.1880975] for details.<br />
<br />
'''UPDATE May 2017''': The second version of the RKI MALDI-ToF MS database is available (Creatives Commons license, CC-BY-NC-SA), see [http://doi.org/10.5281/zenodo.582602 http://doi.org/10.5281/zenodo.582602] for details.<br />
<br />
'''UPDATE Oct 2016''': Since October 27, 2016 the database from the Robert Koch Institute (RKI) with MALDI-ToF mass spectra from the genera ''Bacillus'', ''Yersinia'' and ''Burkholderia'' is available for download (Zenodo, Creatives Commons license, CC-BY-NC-SA). The RKI database currently comprises 5531 spectra in the Bruker data format and the respective peak list file (*.pkf data format) allowing microbial identification using MicrobeMS version 0.80 and later, see the publication [http://doi.org/10.5281/zenodo.163517 ''A MALDI-ToF Mass Spectrometry Database for Identification and Classification of Highly Pathogenic Microorganisms from the Robert Koch Institute (RKI)''].<br />
<br />
== What is a database spectrum? ==<br />
<br />
A database (db) spectrum is a spectrum created from individual mass spectra, ideally containing the spectral variances of biological and technical replicate spectra. Spectra used to construct a database spectrum are ideally collected from identical or at least taxonomically closely related microbial strains. Database spectra are created from pre-processed spectra and their peak tables using standardized parameters (see the description of [[Create database spectra|database spectra]] for more details).</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Frequently_Asked_Questions_(FAQ)&diff=1153Frequently Asked Questions (FAQ)2026-05-01T10:01:50Z<p>Laschp: /* What is the most actual version of MicrobeMS? */</p>
<hr />
<div>== What is MicrobeMS? ==<br />
<br />
The MicrobeMS software package is a program initially designed for the analysis of MALDI-ToF mass spectra of microbial samples. The MicrobeMS software was developed by Peter Lasch at the [http://www.rki.de/EN/Home/homepage_node.html: Robert-Koch-Institute (RKI)] in Berlin, Germany, and can be used to identify microbial strains and species based on their mass spectral patterns (MALDI-ToF MS and LC-MS).<br />
<br />
== What is the most actual version of MicrobeMS? ==<br />
<br />
The most actual version of the MicrobeMS software is MicrobeMS v. 0.93 from May 2026. The MicrobeMS software is continuously being developed further and can be downloaded [[download_MicrobeMS|here]].<br />
<br />
'''May. 2026''': MicrobeMS v.0.93 released<br />
<br />
* Minor edits: peak labels, error reporting, functionality ''more'' in cmpr, increased accuracy of peak detection, etc. <br />
* Many code improvements & bug fixes<br />
<br />
'''Jan. 2026''': MicrobeMS v.0.92<br />
<br />
* [[Export XML Data|''XML export filter'']] for exporting MALDI-ToF MS spectrum data in to a format suitable for utilization of the MicrobeNet solution of the CDC's.<br />
* New functionalities of the software function [[Microbial Identification based on Mass Spectral Libraries and Interspectral Distances|''Microbial identification based on mass spectral libraries and interspectral distances'']]: introducing a MBT like identification method<br />
* [[MALDI Quality Tests|Quality test]] function significantly revised<br />
* Many code improvements & bug fixes<br />
<br />
'''Jun. 2025''': MicrobeMS v.0.90<br />
<br />
* Major revisions of the function [[Unsupervised Hierarchical Cluster Analysis|''Unsupervised hierarchical cluster analysis'']] <br />
* Code improvements and bug fixes<br />
<br />
'''Feb. 2025''': MicrobeMS v.0.89<br />
<br />
* Spectral prep-processing functions revised, see [https://wiki-ms.microbe-ms.com/index.php?title=Spectral_Pre-processing ''MicrobeMS - Spectral Pre-processing''] for details<br />
* New function [https://wiki-ms.microbe-ms.com/index.php?title=MALDI_Quality_Tests ''Quality tests''] introduced<br />
* Code improvements and bug fixes<br />
<br />
'''Nov. 2019''': New functions and bug fixes of version 0.82:<br />
<br />
* Further optimization of the function ''[[Microbial Identification based on Mass Spectral Libraries and Interspectral Distances|Microbial identification based on mass spectral libraries and interspectral distances]]'': Speed improvement by a factor of ~2 compared with version 0.80.<br />
* MicrobeMS v. 0.82 allows analysis of LC-MS&sup1; spectra from microorganisms. Identification analysis of the LC-MS&sup1; data requires a synthetic ''in silico'' database of peptide mass data calculated from microbial genomes (see see '''Preprint''' Lasch P, Schneider A, Blumenscheit C and Doellinger J, [https://doi.org/10.1101/870089 ''Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS&sup1;) and in silico Peptide Mass Data]'', bioRxiv (Dec 10, '''2018'''), doi:10.1101/870089.)<br />
* Code improvements and bug fixes<br />
<br />
'''Feb. 2017''': New functions and bug fixes of version 0.80 (selection):<br />
<br />
* Re-designed interface to the NeuroDeveloper, a software for spectral analysis by artificial neural networks<br />
* The import filter for binary Bruker Daltonics spectra files has been completely revised. This filter supports now also importing of MS data calibrated with the function ''cubic enhanced''.<br />
* New design of the function ''[[Microbial Identification based on Mass Spectral Libraries and Interspectral Distances|Microbial identification based on mass spectral libraries and interspectral distances]]'': Matlab code for calculation of inter-spectral distances is now fully vectorized => speed improvement by a factor of ~4.<br />
* Enhanced functionality of the option ''vary calibration parameters''<br />
* Many code improvements & bug fixes.<br />
<br />
== Is there a standalone version of MicrobeMS? ==<br />
<br />
Yes, a standalone version of the MicrobeMS toolbox has been available since November 2016. The MicrobeMS standalone runs on Windows 7/8/8.1/10 and 11. Like previous pcode versions, the stand-alone version of MicrobeMS is based on Matlab, so the free Matlab Compiler Runtime environment is required. Please see [[install_MicrobeMS|How to install MicrobeMS]] and [[download_MicrobeMS|Downloading MicrobeMS]] for more details.<br />
<br />
== MicrobeMS for Linux. Can MicrobeMS be used under Linux? ==<br />
<br />
The first Linux version of MicrobeMS has been released in November 2019. This, and later software versions were tested under Matlab / Debian versions 10 and 11 and are available as a Matlab pcode toolboxes, i.e. requires Matlab plus two Matlab toolboxes (Statistics and Bioinformatics Toolboxes). More information can be found [[install_MicrobeMS|here]].<br><br />
Update Oct 2024: A compiled Linux version (0.88) is available on request. Note that this version requires installation of the Matlab Compiler Runtime (MCR) R2020a.<br />
<br />
== What is the Matlab Compiler Runtime (MCR) and why do I need to install it? ==<br />
<br />
MicrobeMS is Matlab-based software. The Matlab component runtime is a standalone set of shared libraries that enables the execution of compiled Matlab applications or components on computers that do not have Matlab installed. The Matlab Compiler Runtime (MCR) is available at no charge from the Mathworks Web site. It is important that the version of MCR that runs the application on the target computer is compatible with the version of the Matlab compiler used (i.e. '''MCR 2014a Windows 64-bit''' must be installed to use version 0.84 of MicrobeMS [v. 0.82]). Later versions can be installed either as compatible with '''MCR 2014a Windows 64-bit''' with ''microbems.v.089.R2014a.setup.zip'' or '''MCR 2023b Windows 64-bit''' using ''microbems.v.089.R2023b.setup.zip''.<br />
<br />
== Why I do need to install the MCR 2014a 64-bit and not a more recent version? ==<br />
<br><br />
''This question has now been resolved, as a version for MCR 2023b is available since March 2025.''<br><br />
<br><br />
First of all, MicrobeMS for Windows has been compiled with the Matlab compiler of Matlab version R2014a (Windows 64-bit). But why was a more recent compiler version not used? <br />
The answer to this question has two parts:<br><br />
First, new Matlab versions usually introduce new features, while existing features may be modified or even removed. These changes require extensive source code compatibility checks when migrating to a newer Matlab / Matlab compiler version. Second, with the R2014b release, The Mathworks introduced major changes to the underlying graphics libraries, see https://de.mathworks.com/help/matlab/graphics_transition/major-graphics-changes-in-r2014b.html for details. I noticed that these changes caused performance problems on some computers, see https://de.mathworks.com/matlabcentral/answers/203918-slow-plotting-performance-starting-from-matlab-r2014b for an example. <br><br />
With this in mind, I decided to wait for the performance problems to be solved by hardware evolution, i.e. to wait for faster hardware to solve the problem by itself.<br />
<br />
== I have installed MicrobeMS, but I would like to use also spectral databases ==<br />
<br />
Databases of microbial mass spectra are not provided with the software (except some test spectra of selected ''Escherichia coli'' strains). For a limited number of users we provide spectral databases from our ''Yersinia'' and ''Bacillus'' study on personal request (signing of a data transfer agreement - DTA - is required). Please send an email with your request to the following address: [mailto:lasch@microbe-ms.com lasch@microbe-ms.com].<br><br />
<br />
'''UPDATE Jan 2026''': An ''in silico'' MALDI-ToF MS database is available (CC-BY-NC-SA license). This database has been derived from UniprotKB proteomics databases, i.e. ultimately from microbial genomes. This database is still highly experimental and should not be used for diagnostic purposes. More details will follow in the near future.<br />
<br />
'''UPDATE May 2023''': MALDI-ToF MS database version 4 is available, again under the Creatives Commons license (CC-BY-NC-SA). The RKI Database v.4 now contains a total of 11055 MALDI-ToF mass spectra from 1599 microbial strains of highly pathogenic (i.e. biosafety level 3, BSL-3) bacteria such as ''Bacillus anthracis'', ''Brucella melitensis'', ''Yersinia pestis'', ''Burkholderia mallei'' / ''pseudomallei'' and ''Francisella tularensis'' as well as a selection of spectra of their close and distant relatives, for details see https://doi.org/10.5281/zenodo.7702375.<br />
<br />
'''UPDATE Dec 2019''': The concept of microbial identification by means of MALDI-ToF mass spectrometry measurements of cultivated microbial cells and comparison with entries of a spectral library has been adapted for LC-MS&sup1; based microbial identification, see '''Preprint''' Lasch P, Schneider A, Blumenscheit C and Doellinger J, [https://doi.org/10.1101/870089 ''Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS&sup1;) and in silico Peptide Mass Data]'', bioRxiv (Dec 10, '''2018'''), doi:10.1101/870089.<br><br />
The respective ''in silico'' database can be downloaded from Zenodo (1.5 GB!): [https://doi.org/10.5281/zenodo.3573996 ''In silico Database for Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS&sup1;)''] Zenodo, December 13, 2019.<br> (cf. also [[Identification Analysis by Means of LC-MS&sup1; and ''in silico'' Databases|Identification analysis by means of LC-MS&sup1; and ''in silico'' databases]]).<br />
<br />
'''UPDATE Nov 2018''': The third update of the RKI MALDI-ToF MS database is available (Creatives Commons license, CC-BY-NC-SA). <br />
The RKI database v.3 contains a total of 6264 mass spectra of highly pathogenic (i.e. biosafety level 3, BSL-3) bacteria such as ''Bacillus anthracis'', ''Yersinia pestis'', ''Burkholderia mallei'', ''Burkholderia pseudomallei'' and ''Francisella tularensis'' as well as a selection of spectra from their close and more distant relatives. The database can be used as a reference for diagnosis of BSL-3 bacteria using proprietary and free software packages for MALDI-ToF MS-based microbial identification. Spectral data are distributed as a 7-zip archive that contains the original mass spectra in the original data format (Bruker Daltonics), see [https://doi.org/10.5281/zenodo.1880975 https://doi.org/10.5281/zenodo.1880975] for details.<br />
<br />
'''UPDATE May 2017''': The second version of the RKI MALDI-ToF MS database is available (Creatives Commons license, CC-BY-NC-SA), see [http://doi.org/10.5281/zenodo.582602 http://doi.org/10.5281/zenodo.582602] for details.<br />
<br />
'''UPDATE Oct 2016''': Since October 27, 2016 the database from the Robert Koch Institute (RKI) with MALDI-ToF mass spectra from the genera ''Bacillus'', ''Yersinia'' and ''Burkholderia'' is available for download (Zenodo, Creatives Commons license, CC-BY-NC-SA). The RKI database currently comprises 5531 spectra in the Bruker data format and the respective peak list file (*.pkf data format) allowing microbial identification using MicrobeMS version 0.80 and later, see the publication [http://doi.org/10.5281/zenodo.163517 ''A MALDI-ToF Mass Spectrometry Database for Identification and Classification of Highly Pathogenic Microorganisms from the Robert Koch Institute (RKI)''].<br />
<br />
== What is a database spectrum? ==<br />
<br />
A database (db) spectrum is a spectrum created from individual mass spectra, ideally containing the spectral variances of biological and technical replicate spectra. Spectra used to construct a database spectrum are ideally collected from identical or at least taxonomically closely related microbial strains. Database spectra are created from pre-processed spectra and their peak tables using standardized parameters (see the description of [[Create database spectra|database spectra]] for more details).</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Other_MALDI-ToF_MS_Ressources&diff=1152Other MALDI-ToF MS Ressources2026-05-01T09:36:01Z<p>Laschp: </p>
<hr />
<div>Below is a list of resources that may be useful for MALDI-ToF MS-based identification of bacteria, fungi, arthropods, plants, etc. This list is not exhaustive and will be updated regularly. Please report outdated links (''lasch at microbe-ms dot com'').<br><br />
<br />
[[File:MALDI-workflow.png|500px|right|thumb|Workflow of microbial identification using MALDI-ToF MS (Copyright Peter Lasch, RKI Berlin, 2025)]]<br />
<br />
<ul><br />
<li> [https://www.bruker.com/en/applications/microbiology-and-diagnostics/microbiological-research/maldi-biotyper-for-microbial-research.html MALDI Biotyper] (MBT), a commercial solution for microbial research from Bruker Daltonics</li><br />
<br />
<li> [https://www.biomerieux.com/us/en/our-offer/clinical-products/vitek-ms-prime.html VITEK MS PRIME] MALDI-ToF mass spectrometry from bioMérieux for routine microbial identification (commercial)</li><br />
<br />
<li> [https://microbenet.cdc.gov/ MicrobeNet], a free online resource maintained by the Centers for Disease Control and Prevention (CDC, Atlanta, USA)</li><br />
<br />
<li> [https://spectrometrylab.wordpress.com/ Open Source Spectrometry] - Matthias Mailänder's Blog (OpenChrom, Lablicate)</li><br />
<br />
<li> [https://maldi-up.ua-bw.de/index.asp MALDI-UP] - a free catalogue enabling the exchange of MALDI-TOF-MS spectra between users working in the field of microbiology, food analytics and in other fields, hosted at the CVUA Stuttgart</li><br />
<br />
<li> [https://www.longdom.org/open-access/biospean-a-freeware-tool-for-processing-spectra-from-maldi-intact-cellspore-mass-spectrometry-33447.html Biospean] - a freeware tool for processing spectra from MALDI intact cell/spore mass spectrometry</li><br />
<br />
<li> [https://idbac.org/ IDBac] - a place to ID bacteria, organize strain collections & ask research questions. Registration required. </li><br />
<br />
<li> [https://mabritec.com/en/ Mabritec & Mabriteccentral] - comprehensive ''in silico'' MALDI-ToF MS databases as attractive alternatives for fast, accurate and cost-effective germ identification<br />
<br />
<li> [https://maldibot.ar/ MALDI-BOT] - an AI assistant specialized in interpretation of mass spectrometry results (RENAEM, Argentina)<br />
<br />
<li> [https://msi.happy-dev.fr/ MSI Happy] - free online identification of arthropods, fungi, amanita, alternaria, and bacteria. The platform was developed by Assistance Publique-Hôpitaux de Paris, Sorbonne University, and the BCCM/IHEM/Sciensano collection in Brussels. Registration required<br />
<br />
</ul><br />
<br />
<!-- externe MALDI Datenbanken und MPS Sammlungen--> <br />
<br />
<!-- chinesische Hersteller von MS Lösungen --> <br />
<br />
<!-- Andromas? --><br />
<br />
<!-- nachschauen: https://maldi-up.ua-bw.de/tools.asp --></div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Other_MALDI-ToF_MS_Ressources&diff=1151Other MALDI-ToF MS Ressources2026-05-01T09:35:33Z<p>Laschp: </p>
<hr />
<div>Below is a list of resources that may be useful for MALDI-ToF MS-based identification of bacteria, fungi, arthropods, plants, etc. This list is not exhaustive and will be updated regularly. Please report outdated links (''lasch at microbe-ms dot com'').<br><br />
<br />
[[File:MALDI-workflow.png|500px|right|thumb|Workflow of microbial identification using MALDI-ToF MS (Copyright Peter Lasch, RKI Berlin, 2025)]]<br />
<br />
<ul><br />
<li> [https://www.bruker.com/en/applications/microbiology-and-diagnostics/microbiological-research/maldi-biotyper-for-microbial-research.html MALDI Biotyper] (MBT), a commercial solution for microbial research from Bruker Daltonics</li><br />
<br />
<li> [https://www.biomerieux.com/us/en/our-offer/clinical-products/vitek-ms-prime.html VITEK MS PRIME] MALDI-ToF mass spectrometry from bioMérieux for routine microbial identification (commercial)</li><br />
<br />
<li> [https://microbenet.cdc.gov/ MicrobeNet], a free online resource maintained by the Centers for Disease Control and Prevention (CDC, Atlanta, USA)</li><br />
<br />
<li> [https://spectrometrylab.wordpress.com/ Open Source Spectrometry] - Matthias Mailänder's Blog (OpenChrom, Lablicate)</li><br />
<br />
<li> [https://maldi-up.ua-bw.de/index.asp MALDI-UP] - a free catalogue enabling the exchange of MALDI-TOF-MS spectra between users working in the field of microbiology, food analytics and in other fields, hosted at the CVUA Stuttgart</li><br />
<br />
<li> [https://www.longdom.org/open-access/biospean-a-freeware-tool-for-processing-spectra-from-maldi-intact-cellspore-mass-spectrometry-33447.html Biospean] - a freeware tool for processing spectra from MALDI intact cell/spore mass spectrometry</li><br />
<br />
<li> [https://idbac.org/ IDBac] - a place to ID bacteria, organize strain collections & ask research questions. Registration required. </li><br />
<br />
<li> [https://mabritec.com/en/ Mabritec & Mabriteccentral] - comprehensive ''in silico'' MALDI-ToF MS databases as attractive alternatives for fast, accurate and cost-effective germ identification<br />
<br />
<li> [https://maldibot.ar/ MALDI-BOT] - an AI assistant specialized in interpretation of mass spectrometry results (RENAEM, Argentina)<br />
<br />
<li> [https://msi.happy-dev.fr// MSI Happy] - free online identification of arthropods, fungi, amanita, alternaria, and bacteria. The platform was developed by Assistance Publique-Hôpitaux de Paris, Sorbonne University, and the BCCM/IHEM/Sciensano collection in Brussels. Registration required<br />
<br />
</ul><br />
<br />
<!-- externe MALDI Datenbanken und MPS Sammlungen--> <br />
<br />
<!-- chinesische Hersteller von MS Lösungen --> <br />
<br />
<!-- Andromas? --><br />
<br />
<!-- nachschauen: https://maldi-up.ua-bw.de/tools.asp --></div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Other_MALDI-ToF_MS_Ressources&diff=1150Other MALDI-ToF MS Ressources2026-05-01T09:34:29Z<p>Laschp: </p>
<hr />
<div>Below is a list of resources that may be useful for MALDI-ToF MS-based identification of bacteria. This list is not exhaustive and will be updated regularly. Please report outdated links (''lasch at microbe-ms dot com'').<br><br />
<br />
[[File:MALDI-workflow.png|500px|right|thumb|Workflow of microbial identification using MALDI-ToF MS (Copyright Peter Lasch, RKI Berlin, 2025)]]<br />
<br />
<ul><br />
<li> [https://www.bruker.com/en/applications/microbiology-and-diagnostics/microbiological-research/maldi-biotyper-for-microbial-research.html MALDI Biotyper] (MBT), a commercial solution for microbial research from Bruker Daltonics</li><br />
<br />
<li> [https://www.biomerieux.com/us/en/our-offer/clinical-products/vitek-ms-prime.html VITEK MS PRIME] MALDI-ToF mass spectrometry from bioMérieux for routine microbial identification (commercial)</li><br />
<br />
<li> [https://microbenet.cdc.gov/ MicrobeNet], a free online resource maintained by the Centers for Disease Control and Prevention (CDC, Atlanta, USA)</li><br />
<br />
<li> [https://spectrometrylab.wordpress.com/ Open Source Spectrometry] - Matthias Mailänder's Blog (OpenChrom, Lablicate)</li><br />
<br />
<li> [https://maldi-up.ua-bw.de/index.asp MALDI-UP] - a free catalogue enabling the exchange of MALDI-TOF-MS spectra between users working in the field of microbiology, food analytics and in other fields, hosted at the CVUA Stuttgart</li><br />
<br />
<li> [https://www.longdom.org/open-access/biospean-a-freeware-tool-for-processing-spectra-from-maldi-intact-cellspore-mass-spectrometry-33447.html Biospean] - a freeware tool for processing spectra from MALDI intact cell/spore mass spectrometry</li><br />
<br />
<li> [https://idbac.org/ IDBac] - a place to ID bacteria, organize strain collections & ask research questions. Registration required. </li><br />
<br />
<li> [https://mabritec.com/en/ Mabritec & Mabriteccentral] - comprehensive ''in silico'' MALDI-ToF MS databases as attractive alternatives for fast, accurate and cost-effective germ identification<br />
<br />
<li> [https://maldibot.ar/ MALDI-BOT] - an AI assistant specialized in interpretation of mass spectrometry results (RENAEM, Argentina)<br />
<br />
<li> [https://msi.happy-dev.fr// MSI Happy] - free online identification of arthropods, fungi, amanita, alternaria, and bacteria. The platform was developed by Assistance Publique-Hôpitaux de Paris, Sorbonne University, and the BCCM/IHEM/Sciensano collection in Brussels. Registration required<br />
<br />
</ul><br />
<br />
<!-- externe MALDI Datenbanken und MPS Sammlungen--> <br />
<br />
<!-- chinesische Hersteller von MS Lösungen --> <br />
<br />
<!-- Andromas? --><br />
<br />
<!-- nachschauen: https://maldi-up.ua-bw.de/tools.asp --></div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Other_MALDI-ToF_MS_Ressources&diff=1149Other MALDI-ToF MS Ressources2026-05-01T09:33:15Z<p>Laschp: </p>
<hr />
<div>Below is a list of resources that may be useful for MALDI-ToF MS-based identification of bacteria. This list is not exhaustive and will be updated regularly. Please report outdated links (''lasch at microbe-ms dot com'').<br><br />
<br />
[[File:MALDI-workflow.png|500px|right|thumb|Workflow of microbial identification using MALDI-ToF MS (Copyright Peter Lasch, RKI Berlin, 2025)]]<br />
<br />
<ul><br />
<li> [https://www.bruker.com/en/applications/microbiology-and-diagnostics/microbiological-research/maldi-biotyper-for-microbial-research.html MALDI Biotyper] (MBT), a commercial solution for microbial research from Bruker Daltonics</li><br />
<br />
<li> [https://www.biomerieux.com/us/en/our-offer/clinical-products/vitek-ms-prime.html VITEK MS PRIME] MALDI-ToF mass spectrometry from bioMérieux for routine microbial identification (commercial)</li><br />
<br />
<li> [https://microbenet.cdc.gov/ MicrobeNet], a free online resource maintained by the Centers for Disease Control and Prevention (CDC, Atlanta, USA)</li><br />
<br />
<li> [https://spectrometrylab.wordpress.com/ Open Source Spectrometry] - Matthias Mailänder's Blog (OpenChrom, Lablicate)</li><br />
<br />
<li> [https://maldi-up.ua-bw.de/index.asp MALDI-UP] - a free catalogue enabling the exchange of MALDI-TOF-MS spectra between users working in the field of microbiology, food analytics and in other fields, hosted at the CVUA Stuttgart</li><br />
<br />
<li> [https://www.longdom.org/open-access/biospean-a-freeware-tool-for-processing-spectra-from-maldi-intact-cellspore-mass-spectrometry-33447.html Biospean] - a freeware tool for processing spectra from MALDI intact cell/spore mass spectrometry</li><br />
<br />
<li> [https://idbac.org/ IDBac] - a place to ID bacteria, organize strain collections & ask research questions </li><br />
<br />
<li> [https://mabritec.com/en/ Mabritec & Mabriteccentral] - comprehensive ''in silico'' MALDI-ToF MS databases as attractive alternatives for fast, accurate and cost-effective germ identification<br />
<br />
<li> [https://maldibot.ar/ MALDI-BOT] - an AI assistant specialized in interpretation of mass spectrometry results (RENAEM, Argentina)<br />
<br />
<li> [https://msi.happy-dev.fr// MSI Happy] - online identification of arthropods, fungi, amanita, alternaria, and bacteria. The platform was developed by Assistance Publique-Hôpitaux de Paris, Sorbonne University, and the BCCM/IHEM/Sciensano collection in Brussels.<br />
<br />
</ul><br />
<br />
<!-- externe MALDI Datenbanken und MPS Sammlungen--> <br />
<br />
<!-- chinesische Hersteller von MS Lösungen --> <br />
<br />
<!-- Andromas? --><br />
<br />
<!-- nachschauen: https://maldi-up.ua-bw.de/tools.asp --></div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=MicrobeMS_-_A_Matlab_Toolbox_for_Microbial_Identification_Based_on_Mass_Spectrometry&diff=1148MicrobeMS - A Matlab Toolbox for Microbial Identification Based on Mass Spectrometry2026-05-01T09:14:23Z<p>Laschp: /* Identification and Classification */</p>
<hr />
<div>== Introduction ==<br />
<br />
The MicrobeMS software package is a program specifically designed for the analysis of MALDI-ToF mass spectra of microbial samples. The software was developed by [http://www.peter-lasch.de: Peter Lasch] at the [https://www.rki.de Robert-Koch-Institute (RKI)] in Berlin/Germany and can be used to identify microbial species based on their mass spectral patterns. The program is a comprehensive [http://www.mathworks.com: Matlab]-based package that operates under Windows 7/8/8.1/10/11 and LINUX (Debian, MicrobeMS versions later than 0.81). Original MALDI-ToF mass spectra in the format defined by [http://www.bdal.com: Bruker Daltonics] or by [http://www.shimadzu.com: Shimadzu] (via the mzXML data format) can be imported, processed and converted into a Matlab data matrix format specific to the MicrobeMS program.<br />
<br />
The software allows standard mass spectrometry manipulations such as smoothing, baseline correction, normalization, peak detection, auto-calibration to mention some preprocessing functions. Furthermore, functionalities of the software include, among others, microbial identification analysis based on spectral distances and machine learning methods (ML), e.g. by artificial neural networks (ANN) with visualization of the identification results, unsupervised hierarchical cluster analysis, biomarker analysis, pseudo-gel view generation, as well as microbial mass spectra database management including interfaces for organizing mass spectral metadata. Since the software also runs in a full Windows, or LINUX, 64-bit environment, the number of spectra in the data sets is limited only by the amount of available memory (RAM).<br><br />
<br />
== Getting Started ==<br />
* [[download_MicrobeMS|Downloading MicrobeMS]]<br />
* [[computer_specification|Specification of computer configuration]]<br />
* [[install_MicrobeMS|How to install MicrobeMS]]<br />
* [[Screenshot_of_MicrobeMS|Screenshot]] of the main gui<br />
* [[MicrobeMS_Wiki:General_disclaimer |License conditions]]<br />
* [[How_to_Obtain_a_License|How to obtain a license key]]<br />
* [[Mass Spectrometry Databases|Mass spectrometry databases]]<br />
* [[Publications_with_MicrobeMS|Publications with MicrobeMS, acknowledgements]]<br />
* [[Other MALDI-ToF MS Ressources|Other MALDI-ToF MS ressources]]<br />
* [[Frequently_Asked_Questions_(FAQ)|Frequently asked questions (FAQ)]]<br />
<br />
== Management of Metadata Information ==<br />
<br />
* [[Adding / Editing Metadata of MALDI-TOF Mass Spectral Data|Adding / editing metadata of MS data files]] (spectrum metadata, taxonomic information, culture conditions, sample preparation methods, etc.)<br />
<br />
== Description of Data File Formats Specific to MicrobeMS ==<br />
* [[Data_Format_of_Spectral_Multifiles|Description of the format of spectral multifiles (*.muf)]]<br />
* [[Data_Format_of_Peak_List_Files|Description of the format of peak list files (*.pkf)]]<br />
* Description of the format of quality test files (*.mat)<br />
<!-- commented out * [[Format_of_Quality_Test_Result_Files|Description of the format of quality test files (*.mat)]] --><br />
* [[Description of MicrobeMS' main parameter file 'microbems.opt'|Description of the parameter file ''microbems.opt'']]<br />
<br />
== Import and Export of Mass Spectra and Mass Spectral Libraries ==<br />
<br />
* [[Load spectra (Bruker format)|Load spectral data files]] acquired by Bruker Daltonics MALDI-ToF mass spectrometers<br />
* [[Data_Format_of_Spectral_Multifiles|Load / store spectral multifiles (*.muf)]]<br />
* [[Data_Format_of_Peak_List_Files|Load / store peak list files (*.pkf)]]<br />
* [[Store spectra (Bruker format)|Store spectra in a Bruker-specific data format]]<br />
* [[Export spectra to ASCII|Store spectra in a standard ASCII data format]] (export to ASCII)<br />
* [[Store spectra (NeuroDeveloper format)|Store peaklist data in a format specific to the NeuroDeveloper software]] (export to NeuroDeveloper)<br />
* [[Import Mass Spectra in a mzXML Data Format|Import mass spectral data from mzXML data]] (allows importing spectra from Shimadzu/bioMérieux systems)<br />
* [[Export XML Data|Export XML Data]] (required for identification analysis with MicrobeNet from the CDC)<br />
<br />
== Spectral Analysis and Visualization ==<br />
* [[Spectral Pre-processing|Spectral pre-processing]]: smoothing, baseline correction, normalization, cut, auto-calibration, reduce resolution (binning)<br />
* [[MALDI Quality Tests|Quality tests of MALDI-ToF mass spectra]]<br />
* [[Peak Detection|Peak detection]]<br />
* [[Averaging Mass Spectra|Averaging mass spectra]]<br />
* [[Display MS Metadata|Display spectral metadata]]<br />
* [[The Log-File (logfile.txt)|The log-file]] (logfile.txt)<br />
<br />
== Identification and Classification ==<br />
<br />
* [[Unsupervised Hierarchical Cluster Analysis|Unsupervised hierarchical cluster analysis]] <br />
* [[Create database spectra|Creating database spectra from individual microbial mass spectra]]<br />
* Compiling mass spectral databases<br />
* [[Microbial Identification based on Mass Spectral Libraries and Interspectral Distances|Microbial identification based on mass spectral libraries and interspectral distances]]<br />
<!--<br />
* [[Identification Analysis by Neural Networks|Identification analysis by artificial neural networks (ANN,]] requires the NeuroDeveloper software package from [http://www.synthon-analytics.de: Synthon Analytics]) --><br />
* Identification Analysis by Neural Networks, requires the NeuroDeveloper software package from [http://www.synthon-analytics.de: Synthon Analytics])<br />
* [[Identification Analysis by Means of LC-MS&sup1; and ''in silico'' Databases|Identification analysis by means of LC-MS&sup1; and ''in silico'' databases]]<br />
<br />
== Identification of MS Biomarker Peaks ==<br />
<br />
* Generation of [[Creating Pseudo-Gel Views|''pseudo-gel'' views]] from microbial mass spectra<br />
* [[Class Assignment|How to perform class assignments]]<br />
* [[Peak Frequency Test|Peak frequency tests]]<br />
* [[Two-samples t-Tests|Two-samples t-tests]]<br />
* [[Wilcoxon Rank-Sum Test|Wilcoxon rank-sum tests]]</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=MicrobeMS_-_A_Matlab_Toolbox_for_Microbial_Identification_Based_on_Mass_Spectrometry&diff=1147MicrobeMS - A Matlab Toolbox for Microbial Identification Based on Mass Spectrometry2026-05-01T09:14:04Z<p>Laschp: /* Identification and Classification */</p>
<hr />
<div>== Introduction ==<br />
<br />
The MicrobeMS software package is a program specifically designed for the analysis of MALDI-ToF mass spectra of microbial samples. The software was developed by [http://www.peter-lasch.de: Peter Lasch] at the [https://www.rki.de Robert-Koch-Institute (RKI)] in Berlin/Germany and can be used to identify microbial species based on their mass spectral patterns. The program is a comprehensive [http://www.mathworks.com: Matlab]-based package that operates under Windows 7/8/8.1/10/11 and LINUX (Debian, MicrobeMS versions later than 0.81). Original MALDI-ToF mass spectra in the format defined by [http://www.bdal.com: Bruker Daltonics] or by [http://www.shimadzu.com: Shimadzu] (via the mzXML data format) can be imported, processed and converted into a Matlab data matrix format specific to the MicrobeMS program.<br />
<br />
The software allows standard mass spectrometry manipulations such as smoothing, baseline correction, normalization, peak detection, auto-calibration to mention some preprocessing functions. Furthermore, functionalities of the software include, among others, microbial identification analysis based on spectral distances and machine learning methods (ML), e.g. by artificial neural networks (ANN) with visualization of the identification results, unsupervised hierarchical cluster analysis, biomarker analysis, pseudo-gel view generation, as well as microbial mass spectra database management including interfaces for organizing mass spectral metadata. Since the software also runs in a full Windows, or LINUX, 64-bit environment, the number of spectra in the data sets is limited only by the amount of available memory (RAM).<br><br />
<br />
== Getting Started ==<br />
* [[download_MicrobeMS|Downloading MicrobeMS]]<br />
* [[computer_specification|Specification of computer configuration]]<br />
* [[install_MicrobeMS|How to install MicrobeMS]]<br />
* [[Screenshot_of_MicrobeMS|Screenshot]] of the main gui<br />
* [[MicrobeMS_Wiki:General_disclaimer |License conditions]]<br />
* [[How_to_Obtain_a_License|How to obtain a license key]]<br />
* [[Mass Spectrometry Databases|Mass spectrometry databases]]<br />
* [[Publications_with_MicrobeMS|Publications with MicrobeMS, acknowledgements]]<br />
* [[Other MALDI-ToF MS Ressources|Other MALDI-ToF MS ressources]]<br />
* [[Frequently_Asked_Questions_(FAQ)|Frequently asked questions (FAQ)]]<br />
<br />
== Management of Metadata Information ==<br />
<br />
* [[Adding / Editing Metadata of MALDI-TOF Mass Spectral Data|Adding / editing metadata of MS data files]] (spectrum metadata, taxonomic information, culture conditions, sample preparation methods, etc.)<br />
<br />
== Description of Data File Formats Specific to MicrobeMS ==<br />
* [[Data_Format_of_Spectral_Multifiles|Description of the format of spectral multifiles (*.muf)]]<br />
* [[Data_Format_of_Peak_List_Files|Description of the format of peak list files (*.pkf)]]<br />
* Description of the format of quality test files (*.mat)<br />
<!-- commented out * [[Format_of_Quality_Test_Result_Files|Description of the format of quality test files (*.mat)]] --><br />
* [[Description of MicrobeMS' main parameter file 'microbems.opt'|Description of the parameter file ''microbems.opt'']]<br />
<br />
== Import and Export of Mass Spectra and Mass Spectral Libraries ==<br />
<br />
* [[Load spectra (Bruker format)|Load spectral data files]] acquired by Bruker Daltonics MALDI-ToF mass spectrometers<br />
* [[Data_Format_of_Spectral_Multifiles|Load / store spectral multifiles (*.muf)]]<br />
* [[Data_Format_of_Peak_List_Files|Load / store peak list files (*.pkf)]]<br />
* [[Store spectra (Bruker format)|Store spectra in a Bruker-specific data format]]<br />
* [[Export spectra to ASCII|Store spectra in a standard ASCII data format]] (export to ASCII)<br />
* [[Store spectra (NeuroDeveloper format)|Store peaklist data in a format specific to the NeuroDeveloper software]] (export to NeuroDeveloper)<br />
* [[Import Mass Spectra in a mzXML Data Format|Import mass spectral data from mzXML data]] (allows importing spectra from Shimadzu/bioMérieux systems)<br />
* [[Export XML Data|Export XML Data]] (required for identification analysis with MicrobeNet from the CDC)<br />
<br />
== Spectral Analysis and Visualization ==<br />
* [[Spectral Pre-processing|Spectral pre-processing]]: smoothing, baseline correction, normalization, cut, auto-calibration, reduce resolution (binning)<br />
* [[MALDI Quality Tests|Quality tests of MALDI-ToF mass spectra]]<br />
* [[Peak Detection|Peak detection]]<br />
* [[Averaging Mass Spectra|Averaging mass spectra]]<br />
* [[Display MS Metadata|Display spectral metadata]]<br />
* [[The Log-File (logfile.txt)|The log-file]] (logfile.txt)<br />
<br />
== Identification and Classification ==<br />
<br />
* [[Unsupervised Hierarchical Cluster Analysis|Unsupervised hierarchical cluster analysis]] <br />
* [[Create database spectra|Creating database spectra from individual microbial mass spectra]]<br />
* Compiling mass spectral databases<br />
* [[Microbial Identification based on Mass Spectral Libraries and Interspectral Distances|Microbial identification based on mass spectral libraries and interspectral distances]]<br />
<!--<br />
* [[Identification Analysis by Neural Networks|Identification analysis by artificial neural networks (ANN,]] requires the NeuroDeveloper software package from [http://www.synthon-analytics.de: Synthon Analytics]) --><br />
* Identification Analysis by Neural Networks, requires the NeuroDeveloper software package from [http://www.synthon-analytics.de: Synthon Analytics]) --><br />
* [[Identification Analysis by Means of LC-MS&sup1; and ''in silico'' Databases|Identification analysis by means of LC-MS&sup1; and ''in silico'' databases]]<br />
<br />
== Identification of MS Biomarker Peaks ==<br />
<br />
* Generation of [[Creating Pseudo-Gel Views|''pseudo-gel'' views]] from microbial mass spectra<br />
* [[Class Assignment|How to perform class assignments]]<br />
* [[Peak Frequency Test|Peak frequency tests]]<br />
* [[Two-samples t-Tests|Two-samples t-tests]]<br />
* [[Wilcoxon Rank-Sum Test|Wilcoxon rank-sum tests]]</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Data_Format_of_Peak_List_Files&diff=1146Data Format of Peak List Files2026-03-09T10:02:02Z<p>Laschp: /* Database spectra - C.dbs */</p>
<hr />
<div>Peak list files combine multiple peak lists in one single file. Such peak list files are stored in a Matlab&trade; specific data format and contain peak data as well as the respective metadata. Peak list files can be loaded by entering the following command at the Matlab command prompt:<br />
<br />
>> load('pkffname','-mat');<br />
<br />
where ''pkffname'' denotes the name of the peak list multifile. For example, the command ''load('RKI-ring-trial-test-data.pkf','-mat')'' will open the file ''RKI-ring-trial-test-data.pkf'', a MALDI-ToF mass peak list multifile containing 24 individual peak tables acquired from experimental MALDI-ToF mass spectra. The latter spectra were recorded within the ''so called'' [https://pubmed.ncbi.nlm.nih.gov/26063856/ '''RKI ring trial study''']. The file ''RKI-ring-trial-test-data.pkf'' can be downloaded [https://wiki.microbe-ms.com/upload/RKI-ring-trial-test-data.pkf: '''here''']. <br><br />
You will have access to a new Matlab variable ''C'' (struc array) if loading was successful. Details of the structure of ''C'' are described next.<br> &nbsp; <br><br />
<br />
<br />
== Fields of the structure array - '''''C''''' ==<br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Data type<br />
!width=300|<br />
|-<br />
| nam<br />
| spectra id<br />
| char array<br />
| rowspan="39" style="background: #ffffff;" valign="top" | [[File:Multifile-format-spec-struc.png|250px|thumb|center|Screenshot showing the contents of the structure array ''C'' that is stored in ''so called'' spectrum multi files (*.muf). Fields of ''C'' contain spectral data (original, i.e. unmodified, and pre-processed), spectrum metadata as well as peak lists, calibration information, results of quality tests, and information collected during creation of average, or database spectra. The example screenshot shows the contents of a database spectrum.]]<br />
|-<br />
| gen<br />
| genus information<br />
| char array<br />
|-<br />
| spe<br />
| species info<br />
| char array<br />
|-<br />
| str<br />
| strain info<br />
| char array<br />
|-<br />
| typ<br />
| type<br />
| char array<br />
|-<br />
| uid<br />
| taxonomy identification number for species as used by the NCBI (see [https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi]), can be modified<br />
| char array<br />
|-<br />
| uie<br />
| unmodified taxonomy identification number for strains used by the NCBI (see [https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi])<br />
| char array<br />
|-<br />
| gti<br />
| cultivation conditions: growth time<br />
| char array<br />
|-<br />
| tem<br />
| cultivation conditions: cultivation temperature<br />
| char array<br />
|-<br />
| air<br />
| cultivation conditions: cultivation under aerobic or anaerobic conditions<br />
| char array<br />
|-<br />
| med<br />
| cultivation conditions: cultivation medium<br />
| char array<br />
|-<br />
| spo<br />
| spore formers (Yes or No)<br />
| char array<br />
|-<br />
| con<br />
| sample concentration<br />
| char array<br />
|-<br />
| trt <br />
| sample treatment<br />
| char array<br />
|-<br />
| ext <br />
| extra information<br />
| char array<br />
|-<br />
| las <br />
| laser parameters (power, spot diameter, frequency, etc.)<br />
| char array<br />
|-<br />
| cal <br />
| calibration info<br />
| char array<br />
|-<br />
| met<br />
| measurement method<br />
| char array<br />
|-<br />
| cus <br />
| customer info<br />
| char array<br />
|-<br />
| tim <br />
| date and time of measurement<br />
| char array<br />
|-<br />
| pth<br />
| path to spectrum<br />
| char array<br />
|-<br />
| cls<br />
| class assignment (valid values are 0,1,2,3 and 4)<br />
| float32<br />
|-<br />
| lst<br />
| formatted text containing the peak table info<br />
| char array<br />
|-<br />
| seq<br />
| sequence of pre-processing steps<br />
| char array<br />
|-<br />
| smo<br />
| the number of smoothing points (Savitzky-Golay smoothing)<br />
| char array<br />
|-<br />
| bas<br />
| number of intervals used for baseline correction<br />
| float32<br />
|-<br />
| nrm<br />
| normalization parameter (Yes:1, No:0)<br />
| float32<br />
|-<br />
| clb<br />
| calibration parameters (not used)<br />
| float32<br />
|-<br />
| red<br />
| data reduction factor (spectral binning)<br />
| char array<br />
|-<br />
| cut<br />
| cut in the spectral domain, m/z range<br />
| char array<br />
|-<br />
| tmp<br />
| temporary info (not always present)<br />
| char array<br />
|-<br />
| mod<br />
| original data modified by cut spectra or reduce resolution (Yes:1, No:0)<br />
| float32<br />
|-<br />
| lms<br />
| MALDI-ToF MS, or LC-MS&sup1; data? (0: MALDI, 1: LC-MS&sup1;)<br />
| float32<br />
|-<br />
| pik<br />
| [[#peak table format|peak table]], an array of the dimension [4 x npeaks] or [6 x npeaks], where npeaks denotes the number of peaks <br />
| float 32<br />
|-<br />
| ccl<br />
| [[#structure array ccl|calibration information]]<br />
| struc array<br />
|-<br />
| avr<br />
| [[#structure array avr|average spectrum]]<br />
| struc array<br />
|-<br />
| dbs<br />
| [[#structure array dbs|data base spectrum]]<br />
| struc array<br />
|-<br />
| prm<br />
| parameters of peak detection<br />
| char array<br />
|-<br />
| qt<br />
| quality test parameter<br />
| struc array<br />
|-<br />
|}<br />
<br />
== Peak table format - '''''C.pik''''' ==<br />
<br />
<span class="mw-headline" id="peak table format"></span><br />
<br><br />
{| class="wikitable" width=800<br />
!width=100| Fields<br />
!width=700| Description<br />
|-<br />
| C.pik(1,:) <br> &nbsp; <br><br />
| m/z positions of the peaks in the peak table <br> &nbsp; <br> <br />
|-<br />
| C.pik(2,:) <br> &nbsp; <br><br />
| absolute intensities of these peaks <br> &nbsp; <br><br />
|-<br />
| C.pik(3,:) <br> &nbsp; <br><br />
| weighting factors (the sum of these factors equals 100) <br> &nbsp; <br><br />
|-<br />
| C.pik(4,:) <br> &nbsp; <br><br />
| in case of single spectra, i.e. no database or average spectra: baseline-corrected absolute intensities of the peaks, in case of average or database spectra: the relative peak frequency<br />
|-<br />
| C.pik(5,:) <br> &nbsp; <br><br />
| FWHH of the given peak (not always present, requires QT) <br> &nbsp; <br><br />
|-<br />
| C.pik(6,:) <br> &nbsp; <br><br />
| resolving power of the given peak (not always present, requires QT) <br> &nbsp; <br><br />
|}<br />
<br />
== Calibration information - '''''C.ccl''''' ==<br />
<br />
<span class="mw-headline" id="structure array ccl"></span><br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| cl1<br />
| calibration constant 1<br />
| float32<br />
| rowspan="15" style="background: #ffffff;" valign="top" | [[File:calibration-format-spec-struc.png|250px|thumb|center|Screenshot showing the contents of the structure array ''C.ccl'' containing the calibration info (calibration constants, delay time, number of spectrum data points, etc.)]]<br />
|-<br />
| cl2<br />
| calibration constant 2<br />
| float32<br />
|-<br />
| cl3<br />
| calibration constant 3<br />
| float32<br />
|-<br />
| del <br />
| delay time [ns]<br />
| float32<br />
|-<br />
| npt<br />
| number of data points<br />
| float32<br />
|-<br />
| res <br />
| time resolution [ns]<br />
| float32<br />
|-<br />
| ncl<br />
| calibration info required to store the spectrum in a Bruker-specific data format <br />
| char array<br />
|-<br />
| ncr<br />
| calibration info required to store the spectrum in a Bruker-specific data format <br />
| char array<br />
|-<br />
| bid<br />
| hardware id of the spectrum ('Bruker ID')<br />
| char array<br />
|-<br />
| mid<br />
| MicrobeMS id of the spectrum<br />
| char array<br />
|-<br />
| org<br />
| manufacturer info<br />
| char array<br />
|-<br />
| tfu<br />
| 'ToF user'<br />
| char array<br />
|-<br />
| spm<br />
| not used<br />
| char array<br />
|-<br />
| stp<br />
| type of measurement (should be 'TOF')<br />
| char array<br />
|-<br />
| acq<br />
| further acquisition info<br />
| char array<br />
|}<br />
<br />
== Database spectra - '''''C.dbs''''' ==<br />
<br />
<span class="mw-headline" id="structure array dbs"></span><br />
<br><br />
A [[Create database spectra|database spectrum]] is usually created from many (>3) individual mass spectra. Like in regular experimental spectra, spectral data and metadata of average spectra are stored in specific fields of structure array ''C''. In database spectra the field ''C(i).dbs'' is used to store relevant data from experimental source spectra from which the given database spectrum has been derived. These fields are left empty in experimental and average spectra. Details of the structure of ''C.dbs'' are given in the table below. <br />
<br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| mem<br />
| specifies whether the current spectrum is a data base spectrum (1) or not (0)<br />
| char array<br />
| rowspan="5" style="background: #ffffff;" valign="top" |[[File:dbs-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''C.dbs''. This screenshot shows information like the spectrum id, taxonomic information, peak tables, respective peak detection parameters, etc of mass spectrum #1 [C(1).dbs(1,1)] that was used with others to obtain a database spectrum]]<br />
|-<br />
| ids<br />
| ID's of the individual mass spectra that contributed to the given database spectrum<br />
| char array<br />
|-<br />
| tax<br />
| contains taxonomical information (i.e. the genus, species, strain information)<br />
| char array<br />
|-<br />
| pik<br />
| peak table of the given source spectrum <br />
| float32<br />
|-<br />
| prm<br />
| parameters used for peak detection <br />
| char array<br />
|}<br />
<br />
== Average spectra - '''''C.avr''''' ==<br />
<br />
<span class="mw-headline" id="structure array avr"></span><br />
<br><br />
An [[Averaging Mass Spectra|average spectrum]] is usually created from many (>3) individual mass spectra. Like in regular experimental spectra, spectral data and metadata of average spectra are stored in specific fields of structure array ''C''. In average spectra the field ''C(i).avr'' is used to store relevant data from experimental source spectra from which the given average spectrum has been derived. These fields are empty in experimental and database spectra. Details of the structure of ''C.avr'' are given in the table below. <br />
<br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| mem<br />
| specifies whether the contributing spectrum is an average spectrum (1) or not (0)<br />
| char array<br />
| rowspan="6" style="background: #ffffff;" valign="top" |[[File:avr-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''C.avr''. This screenshot shows information like the spectrum id, taxonomic information, peak tables, respective peak detection parameters, etc of mass spectrum #1 [C(1).avr(1,1)] that was used with others to obtain an average spectrum]]<br />
|-<br />
| ids<br />
| ID's of the individual mass spectra that contributed to the given average spectrum<br />
| char array<br />
|-<br />
| tax<br />
| contains taxonomical information (i.e. the genus, species, strain information)<br />
| char array<br />
|-<br />
| pik<br />
| peak table of the given source spectrum <br />
| float32<br />
|-<br />
| prm<br />
| parameters used for peak detection <br />
| char array<br />
|}<br />
<br />
== Quality test results - '''''C.qt''''' ==<br />
<br />
<span class="mw-headline" id="structure array qt"></span><br />
<br><br />
The structure array ''C.qt'' contains the results of a [[MALDI Quality Tests|Quality Test]]. Fields of this structure are empty if no QT has been performed. Details of the structure of ''C.qt'' are given in the table below. <br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| noise<br />
| QT data of the ''noise'' test, contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
| rowspan="7" style="background: #ffffff;" valign="top" |[[File:qt-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''C.qt'' that contains the results of a quality test (QT).]]<br />
|-<br />
| basln<br />
| QT data of the ''baseline'' test, contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| npiks<br />
| QT data of the test ''number of peaks'', contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| respw<br />
| QT data of the test ''resolution power'', contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| rnk<br />
| overall rank the given spectrum has achieved in a QT with a number of other spectra<br />
| float32<br />
|-<br />
| res<br />
| overall quality test score<br />
| float32<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Data_Format_of_Peak_List_Files&diff=1145Data Format of Peak List Files2026-03-09T10:01:37Z<p>Laschp: /* Average spectra - C.avr */</p>
<hr />
<div>Peak list files combine multiple peak lists in one single file. Such peak list files are stored in a Matlab&trade; specific data format and contain peak data as well as the respective metadata. Peak list files can be loaded by entering the following command at the Matlab command prompt:<br />
<br />
>> load('pkffname','-mat');<br />
<br />
where ''pkffname'' denotes the name of the peak list multifile. For example, the command ''load('RKI-ring-trial-test-data.pkf','-mat')'' will open the file ''RKI-ring-trial-test-data.pkf'', a MALDI-ToF mass peak list multifile containing 24 individual peak tables acquired from experimental MALDI-ToF mass spectra. The latter spectra were recorded within the ''so called'' [https://pubmed.ncbi.nlm.nih.gov/26063856/ '''RKI ring trial study''']. The file ''RKI-ring-trial-test-data.pkf'' can be downloaded [https://wiki.microbe-ms.com/upload/RKI-ring-trial-test-data.pkf: '''here''']. <br><br />
You will have access to a new Matlab variable ''C'' (struc array) if loading was successful. Details of the structure of ''C'' are described next.<br> &nbsp; <br><br />
<br />
<br />
== Fields of the structure array - '''''C''''' ==<br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Data type<br />
!width=300|<br />
|-<br />
| nam<br />
| spectra id<br />
| char array<br />
| rowspan="39" style="background: #ffffff;" valign="top" | [[File:Multifile-format-spec-struc.png|250px|thumb|center|Screenshot showing the contents of the structure array ''C'' that is stored in ''so called'' spectrum multi files (*.muf). Fields of ''C'' contain spectral data (original, i.e. unmodified, and pre-processed), spectrum metadata as well as peak lists, calibration information, results of quality tests, and information collected during creation of average, or database spectra. The example screenshot shows the contents of a database spectrum.]]<br />
|-<br />
| gen<br />
| genus information<br />
| char array<br />
|-<br />
| spe<br />
| species info<br />
| char array<br />
|-<br />
| str<br />
| strain info<br />
| char array<br />
|-<br />
| typ<br />
| type<br />
| char array<br />
|-<br />
| uid<br />
| taxonomy identification number for species as used by the NCBI (see [https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi]), can be modified<br />
| char array<br />
|-<br />
| uie<br />
| unmodified taxonomy identification number for strains used by the NCBI (see [https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi])<br />
| char array<br />
|-<br />
| gti<br />
| cultivation conditions: growth time<br />
| char array<br />
|-<br />
| tem<br />
| cultivation conditions: cultivation temperature<br />
| char array<br />
|-<br />
| air<br />
| cultivation conditions: cultivation under aerobic or anaerobic conditions<br />
| char array<br />
|-<br />
| med<br />
| cultivation conditions: cultivation medium<br />
| char array<br />
|-<br />
| spo<br />
| spore formers (Yes or No)<br />
| char array<br />
|-<br />
| con<br />
| sample concentration<br />
| char array<br />
|-<br />
| trt <br />
| sample treatment<br />
| char array<br />
|-<br />
| ext <br />
| extra information<br />
| char array<br />
|-<br />
| las <br />
| laser parameters (power, spot diameter, frequency, etc.)<br />
| char array<br />
|-<br />
| cal <br />
| calibration info<br />
| char array<br />
|-<br />
| met<br />
| measurement method<br />
| char array<br />
|-<br />
| cus <br />
| customer info<br />
| char array<br />
|-<br />
| tim <br />
| date and time of measurement<br />
| char array<br />
|-<br />
| pth<br />
| path to spectrum<br />
| char array<br />
|-<br />
| cls<br />
| class assignment (valid values are 0,1,2,3 and 4)<br />
| float32<br />
|-<br />
| lst<br />
| formatted text containing the peak table info<br />
| char array<br />
|-<br />
| seq<br />
| sequence of pre-processing steps<br />
| char array<br />
|-<br />
| smo<br />
| the number of smoothing points (Savitzky-Golay smoothing)<br />
| char array<br />
|-<br />
| bas<br />
| number of intervals used for baseline correction<br />
| float32<br />
|-<br />
| nrm<br />
| normalization parameter (Yes:1, No:0)<br />
| float32<br />
|-<br />
| clb<br />
| calibration parameters (not used)<br />
| float32<br />
|-<br />
| red<br />
| data reduction factor (spectral binning)<br />
| char array<br />
|-<br />
| cut<br />
| cut in the spectral domain, m/z range<br />
| char array<br />
|-<br />
| tmp<br />
| temporary info (not always present)<br />
| char array<br />
|-<br />
| mod<br />
| original data modified by cut spectra or reduce resolution (Yes:1, No:0)<br />
| float32<br />
|-<br />
| lms<br />
| MALDI-ToF MS, or LC-MS&sup1; data? (0: MALDI, 1: LC-MS&sup1;)<br />
| float32<br />
|-<br />
| pik<br />
| [[#peak table format|peak table]], an array of the dimension [4 x npeaks] or [6 x npeaks], where npeaks denotes the number of peaks <br />
| float 32<br />
|-<br />
| ccl<br />
| [[#structure array ccl|calibration information]]<br />
| struc array<br />
|-<br />
| avr<br />
| [[#structure array avr|average spectrum]]<br />
| struc array<br />
|-<br />
| dbs<br />
| [[#structure array dbs|data base spectrum]]<br />
| struc array<br />
|-<br />
| prm<br />
| parameters of peak detection<br />
| char array<br />
|-<br />
| qt<br />
| quality test parameter<br />
| struc array<br />
|-<br />
|}<br />
<br />
== Peak table format - '''''C.pik''''' ==<br />
<br />
<span class="mw-headline" id="peak table format"></span><br />
<br><br />
{| class="wikitable" width=800<br />
!width=100| Fields<br />
!width=700| Description<br />
|-<br />
| C.pik(1,:) <br> &nbsp; <br><br />
| m/z positions of the peaks in the peak table <br> &nbsp; <br> <br />
|-<br />
| C.pik(2,:) <br> &nbsp; <br><br />
| absolute intensities of these peaks <br> &nbsp; <br><br />
|-<br />
| C.pik(3,:) <br> &nbsp; <br><br />
| weighting factors (the sum of these factors equals 100) <br> &nbsp; <br><br />
|-<br />
| C.pik(4,:) <br> &nbsp; <br><br />
| in case of single spectra, i.e. no database or average spectra: baseline-corrected absolute intensities of the peaks, in case of average or database spectra: the relative peak frequency<br />
|-<br />
| C.pik(5,:) <br> &nbsp; <br><br />
| FWHH of the given peak (not always present, requires QT) <br> &nbsp; <br><br />
|-<br />
| C.pik(6,:) <br> &nbsp; <br><br />
| resolving power of the given peak (not always present, requires QT) <br> &nbsp; <br><br />
|}<br />
<br />
== Calibration information - '''''C.ccl''''' ==<br />
<br />
<span class="mw-headline" id="structure array ccl"></span><br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| cl1<br />
| calibration constant 1<br />
| float32<br />
| rowspan="15" style="background: #ffffff;" valign="top" | [[File:calibration-format-spec-struc.png|250px|thumb|center|Screenshot showing the contents of the structure array ''C.ccl'' containing the calibration info (calibration constants, delay time, number of spectrum data points, etc.)]]<br />
|-<br />
| cl2<br />
| calibration constant 2<br />
| float32<br />
|-<br />
| cl3<br />
| calibration constant 3<br />
| float32<br />
|-<br />
| del <br />
| delay time [ns]<br />
| float32<br />
|-<br />
| npt<br />
| number of data points<br />
| float32<br />
|-<br />
| res <br />
| time resolution [ns]<br />
| float32<br />
|-<br />
| ncl<br />
| calibration info required to store the spectrum in a Bruker-specific data format <br />
| char array<br />
|-<br />
| ncr<br />
| calibration info required to store the spectrum in a Bruker-specific data format <br />
| char array<br />
|-<br />
| bid<br />
| hardware id of the spectrum ('Bruker ID')<br />
| char array<br />
|-<br />
| mid<br />
| MicrobeMS id of the spectrum<br />
| char array<br />
|-<br />
| org<br />
| manufacturer info<br />
| char array<br />
|-<br />
| tfu<br />
| 'ToF user'<br />
| char array<br />
|-<br />
| spm<br />
| not used<br />
| char array<br />
|-<br />
| stp<br />
| type of measurement (should be 'TOF')<br />
| char array<br />
|-<br />
| acq<br />
| further acquisition info<br />
| char array<br />
|}<br />
<br />
== Database spectra - '''''C.dbs''''' ==<br />
<br />
<span class="mw-headline" id="structure array dbs"></span><br />
<br><br />
A [[Create database spectra|database spectrum]] is usually created from many (>3) individual mass spectra. Like in regular experimental spectra, spectral data and metadata of average spectra are stored in specific fields of structure array ''C''. In database spectra the field ''C(i).dbs'' is used to store relevant data from experimental source spectra from which the given database spectrum has been derived. These fields are left empty in experimental and average spectra. Details of the structure of ''C.dbs'' are given in the table below. <br />
<br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| mem<br />
| specifies whether the current spectrum is a data base spectrum (1) or not (0)<br />
| char array<br />
| rowspan="5" style="background: #ffffff;" valign="top" |[[File:dbs-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''C.dbs''. This screenshot shows information like the spectrum id, taxonomic information, peak tables, respective peak detection parameters, etc of mass spectrum #1 [C(1).dbs(1,1)] that was used with others to obtain a database spectrum]]<br />
|-<br />
| ids<br />
| id of the individual mass spectrum that contributed to the given database spectrum<br />
| char array<br />
|-<br />
| tax<br />
| contains taxonomical information (i.e. the genus, species, strain information)<br />
| char array<br />
|-<br />
| pik<br />
| peak table of the given source spectrum <br />
| float32<br />
|-<br />
| prm<br />
| parameters used for peak detection <br />
| char array<br />
|}<br />
<br />
== Average spectra - '''''C.avr''''' ==<br />
<br />
<span class="mw-headline" id="structure array avr"></span><br />
<br><br />
An [[Averaging Mass Spectra|average spectrum]] is usually created from many (>3) individual mass spectra. Like in regular experimental spectra, spectral data and metadata of average spectra are stored in specific fields of structure array ''C''. In average spectra the field ''C(i).avr'' is used to store relevant data from experimental source spectra from which the given average spectrum has been derived. These fields are empty in experimental and database spectra. Details of the structure of ''C.avr'' are given in the table below. <br />
<br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| mem<br />
| specifies whether the contributing spectrum is an average spectrum (1) or not (0)<br />
| char array<br />
| rowspan="6" style="background: #ffffff;" valign="top" |[[File:avr-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''C.avr''. This screenshot shows information like the spectrum id, taxonomic information, peak tables, respective peak detection parameters, etc of mass spectrum #1 [C(1).avr(1,1)] that was used with others to obtain an average spectrum]]<br />
|-<br />
| ids<br />
| ID's of the individual mass spectra that contributed to the given average spectrum<br />
| char array<br />
|-<br />
| tax<br />
| contains taxonomical information (i.e. the genus, species, strain information)<br />
| char array<br />
|-<br />
| pik<br />
| peak table of the given source spectrum <br />
| float32<br />
|-<br />
| prm<br />
| parameters used for peak detection <br />
| char array<br />
|}<br />
<br />
== Quality test results - '''''C.qt''''' ==<br />
<br />
<span class="mw-headline" id="structure array qt"></span><br />
<br><br />
The structure array ''C.qt'' contains the results of a [[MALDI Quality Tests|Quality Test]]. Fields of this structure are empty if no QT has been performed. Details of the structure of ''C.qt'' are given in the table below. <br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| noise<br />
| QT data of the ''noise'' test, contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
| rowspan="7" style="background: #ffffff;" valign="top" |[[File:qt-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''C.qt'' that contains the results of a quality test (QT).]]<br />
|-<br />
| basln<br />
| QT data of the ''baseline'' test, contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| npiks<br />
| QT data of the test ''number of peaks'', contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| respw<br />
| QT data of the test ''resolution power'', contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| rnk<br />
| overall rank the given spectrum has achieved in a QT with a number of other spectra<br />
| float32<br />
|-<br />
| res<br />
| overall quality test score<br />
| float32<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Data_Format_of_Peak_List_Files&diff=1144Data Format of Peak List Files2026-03-09T10:01:15Z<p>Laschp: /* Quality test results - C.qt */</p>
<hr />
<div>Peak list files combine multiple peak lists in one single file. Such peak list files are stored in a Matlab&trade; specific data format and contain peak data as well as the respective metadata. Peak list files can be loaded by entering the following command at the Matlab command prompt:<br />
<br />
>> load('pkffname','-mat');<br />
<br />
where ''pkffname'' denotes the name of the peak list multifile. For example, the command ''load('RKI-ring-trial-test-data.pkf','-mat')'' will open the file ''RKI-ring-trial-test-data.pkf'', a MALDI-ToF mass peak list multifile containing 24 individual peak tables acquired from experimental MALDI-ToF mass spectra. The latter spectra were recorded within the ''so called'' [https://pubmed.ncbi.nlm.nih.gov/26063856/ '''RKI ring trial study''']. The file ''RKI-ring-trial-test-data.pkf'' can be downloaded [https://wiki.microbe-ms.com/upload/RKI-ring-trial-test-data.pkf: '''here''']. <br><br />
You will have access to a new Matlab variable ''C'' (struc array) if loading was successful. Details of the structure of ''C'' are described next.<br> &nbsp; <br><br />
<br />
<br />
== Fields of the structure array - '''''C''''' ==<br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Data type<br />
!width=300|<br />
|-<br />
| nam<br />
| spectra id<br />
| char array<br />
| rowspan="39" style="background: #ffffff;" valign="top" | [[File:Multifile-format-spec-struc.png|250px|thumb|center|Screenshot showing the contents of the structure array ''C'' that is stored in ''so called'' spectrum multi files (*.muf). Fields of ''C'' contain spectral data (original, i.e. unmodified, and pre-processed), spectrum metadata as well as peak lists, calibration information, results of quality tests, and information collected during creation of average, or database spectra. The example screenshot shows the contents of a database spectrum.]]<br />
|-<br />
| gen<br />
| genus information<br />
| char array<br />
|-<br />
| spe<br />
| species info<br />
| char array<br />
|-<br />
| str<br />
| strain info<br />
| char array<br />
|-<br />
| typ<br />
| type<br />
| char array<br />
|-<br />
| uid<br />
| taxonomy identification number for species as used by the NCBI (see [https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi]), can be modified<br />
| char array<br />
|-<br />
| uie<br />
| unmodified taxonomy identification number for strains used by the NCBI (see [https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi])<br />
| char array<br />
|-<br />
| gti<br />
| cultivation conditions: growth time<br />
| char array<br />
|-<br />
| tem<br />
| cultivation conditions: cultivation temperature<br />
| char array<br />
|-<br />
| air<br />
| cultivation conditions: cultivation under aerobic or anaerobic conditions<br />
| char array<br />
|-<br />
| med<br />
| cultivation conditions: cultivation medium<br />
| char array<br />
|-<br />
| spo<br />
| spore formers (Yes or No)<br />
| char array<br />
|-<br />
| con<br />
| sample concentration<br />
| char array<br />
|-<br />
| trt <br />
| sample treatment<br />
| char array<br />
|-<br />
| ext <br />
| extra information<br />
| char array<br />
|-<br />
| las <br />
| laser parameters (power, spot diameter, frequency, etc.)<br />
| char array<br />
|-<br />
| cal <br />
| calibration info<br />
| char array<br />
|-<br />
| met<br />
| measurement method<br />
| char array<br />
|-<br />
| cus <br />
| customer info<br />
| char array<br />
|-<br />
| tim <br />
| date and time of measurement<br />
| char array<br />
|-<br />
| pth<br />
| path to spectrum<br />
| char array<br />
|-<br />
| cls<br />
| class assignment (valid values are 0,1,2,3 and 4)<br />
| float32<br />
|-<br />
| lst<br />
| formatted text containing the peak table info<br />
| char array<br />
|-<br />
| seq<br />
| sequence of pre-processing steps<br />
| char array<br />
|-<br />
| smo<br />
| the number of smoothing points (Savitzky-Golay smoothing)<br />
| char array<br />
|-<br />
| bas<br />
| number of intervals used for baseline correction<br />
| float32<br />
|-<br />
| nrm<br />
| normalization parameter (Yes:1, No:0)<br />
| float32<br />
|-<br />
| clb<br />
| calibration parameters (not used)<br />
| float32<br />
|-<br />
| red<br />
| data reduction factor (spectral binning)<br />
| char array<br />
|-<br />
| cut<br />
| cut in the spectral domain, m/z range<br />
| char array<br />
|-<br />
| tmp<br />
| temporary info (not always present)<br />
| char array<br />
|-<br />
| mod<br />
| original data modified by cut spectra or reduce resolution (Yes:1, No:0)<br />
| float32<br />
|-<br />
| lms<br />
| MALDI-ToF MS, or LC-MS&sup1; data? (0: MALDI, 1: LC-MS&sup1;)<br />
| float32<br />
|-<br />
| pik<br />
| [[#peak table format|peak table]], an array of the dimension [4 x npeaks] or [6 x npeaks], where npeaks denotes the number of peaks <br />
| float 32<br />
|-<br />
| ccl<br />
| [[#structure array ccl|calibration information]]<br />
| struc array<br />
|-<br />
| avr<br />
| [[#structure array avr|average spectrum]]<br />
| struc array<br />
|-<br />
| dbs<br />
| [[#structure array dbs|data base spectrum]]<br />
| struc array<br />
|-<br />
| prm<br />
| parameters of peak detection<br />
| char array<br />
|-<br />
| qt<br />
| quality test parameter<br />
| struc array<br />
|-<br />
|}<br />
<br />
== Peak table format - '''''C.pik''''' ==<br />
<br />
<span class="mw-headline" id="peak table format"></span><br />
<br><br />
{| class="wikitable" width=800<br />
!width=100| Fields<br />
!width=700| Description<br />
|-<br />
| C.pik(1,:) <br> &nbsp; <br><br />
| m/z positions of the peaks in the peak table <br> &nbsp; <br> <br />
|-<br />
| C.pik(2,:) <br> &nbsp; <br><br />
| absolute intensities of these peaks <br> &nbsp; <br><br />
|-<br />
| C.pik(3,:) <br> &nbsp; <br><br />
| weighting factors (the sum of these factors equals 100) <br> &nbsp; <br><br />
|-<br />
| C.pik(4,:) <br> &nbsp; <br><br />
| in case of single spectra, i.e. no database or average spectra: baseline-corrected absolute intensities of the peaks, in case of average or database spectra: the relative peak frequency<br />
|-<br />
| C.pik(5,:) <br> &nbsp; <br><br />
| FWHH of the given peak (not always present, requires QT) <br> &nbsp; <br><br />
|-<br />
| C.pik(6,:) <br> &nbsp; <br><br />
| resolving power of the given peak (not always present, requires QT) <br> &nbsp; <br><br />
|}<br />
<br />
== Calibration information - '''''C.ccl''''' ==<br />
<br />
<span class="mw-headline" id="structure array ccl"></span><br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| cl1<br />
| calibration constant 1<br />
| float32<br />
| rowspan="15" style="background: #ffffff;" valign="top" | [[File:calibration-format-spec-struc.png|250px|thumb|center|Screenshot showing the contents of the structure array ''C.ccl'' containing the calibration info (calibration constants, delay time, number of spectrum data points, etc.)]]<br />
|-<br />
| cl2<br />
| calibration constant 2<br />
| float32<br />
|-<br />
| cl3<br />
| calibration constant 3<br />
| float32<br />
|-<br />
| del <br />
| delay time [ns]<br />
| float32<br />
|-<br />
| npt<br />
| number of data points<br />
| float32<br />
|-<br />
| res <br />
| time resolution [ns]<br />
| float32<br />
|-<br />
| ncl<br />
| calibration info required to store the spectrum in a Bruker-specific data format <br />
| char array<br />
|-<br />
| ncr<br />
| calibration info required to store the spectrum in a Bruker-specific data format <br />
| char array<br />
|-<br />
| bid<br />
| hardware id of the spectrum ('Bruker ID')<br />
| char array<br />
|-<br />
| mid<br />
| MicrobeMS id of the spectrum<br />
| char array<br />
|-<br />
| org<br />
| manufacturer info<br />
| char array<br />
|-<br />
| tfu<br />
| 'ToF user'<br />
| char array<br />
|-<br />
| spm<br />
| not used<br />
| char array<br />
|-<br />
| stp<br />
| type of measurement (should be 'TOF')<br />
| char array<br />
|-<br />
| acq<br />
| further acquisition info<br />
| char array<br />
|}<br />
<br />
== Database spectra - '''''C.dbs''''' ==<br />
<br />
<span class="mw-headline" id="structure array dbs"></span><br />
<br><br />
A [[Create database spectra|database spectrum]] is usually created from many (>3) individual mass spectra. Like in regular experimental spectra, spectral data and metadata of average spectra are stored in specific fields of structure array ''C''. In database spectra the field ''C(i).dbs'' is used to store relevant data from experimental source spectra from which the given database spectrum has been derived. These fields are left empty in experimental and average spectra. Details of the structure of ''C.dbs'' are given in the table below. <br />
<br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| mem<br />
| specifies whether the current spectrum is a data base spectrum (1) or not (0)<br />
| char array<br />
| rowspan="5" style="background: #ffffff;" valign="top" |[[File:dbs-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''C.dbs''. This screenshot shows information like the spectrum id, taxonomic information, peak tables, respective peak detection parameters, etc of mass spectrum #1 [C(1).dbs(1,1)] that was used with others to obtain a database spectrum]]<br />
|-<br />
| ids<br />
| id of the individual mass spectrum that contributed to the given database spectrum<br />
| char array<br />
|-<br />
| tax<br />
| contains taxonomical information (i.e. the genus, species, strain information)<br />
| char array<br />
|-<br />
| pik<br />
| peak table of the given source spectrum <br />
| float32<br />
|-<br />
| prm<br />
| parameters used for peak detection <br />
| char array<br />
|}<br />
<br />
== Average spectra - '''''C.avr''''' ==<br />
<br />
<span class="mw-headline" id="structure array avr"></span><br />
<br><br />
An [[Averaging Mass Spectra|average spectrum]] is usually created from many (>3) individual mass spectra. Like in regular experimental spectra, spectral data and metadata of average spectra are stored in specific fields of structure array ''C''. In average spectra the field ''C(i).avr'' is used to store relevant data from experimental source spectra from which the given average spectrum has been derived. These fields are empty in experimental and database spectra. Details of the structure of ''C.avr'' are given in the table below. <br />
<br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| mem<br />
| specifies whether the contributing spectrum is an average spectrum (1) or not (0)<br />
| char array<br />
| rowspan="6" style="background: #ffffff;" valign="top" |[[File:avr-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''C.avr''. This screenshot shows information like the spectrum id, taxonomic information, peak tables, respective peak detection parameters, etc of mass spectrum #1 [C(1).avr(1,1)] that was used with others to obtain an average spectrum]]<br />
|-<br />
| ids<br />
| id of the individual mass spectrum that contributed to the given average spectrum<br />
| char array<br />
|-<br />
| tax<br />
| contains taxonomical information (i.e. the genus, species, strain information)<br />
| char array<br />
|-<br />
| pik<br />
| peak table of the given source spectrum <br />
| float32<br />
|-<br />
| prm<br />
| parameters used for peak detection <br />
| char array<br />
|}<br />
<br />
<br />
== Quality test results - '''''C.qt''''' ==<br />
<br />
<span class="mw-headline" id="structure array qt"></span><br />
<br><br />
The structure array ''C.qt'' contains the results of a [[MALDI Quality Tests|Quality Test]]. Fields of this structure are empty if no QT has been performed. Details of the structure of ''C.qt'' are given in the table below. <br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| noise<br />
| QT data of the ''noise'' test, contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
| rowspan="7" style="background: #ffffff;" valign="top" |[[File:qt-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''C.qt'' that contains the results of a quality test (QT).]]<br />
|-<br />
| basln<br />
| QT data of the ''baseline'' test, contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| npiks<br />
| QT data of the test ''number of peaks'', contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| respw<br />
| QT data of the test ''resolution power'', contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| rnk<br />
| overall rank the given spectrum has achieved in a QT with a number of other spectra<br />
| float32<br />
|-<br />
| res<br />
| overall quality test score<br />
| float32<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Format_of_Spectral_Multifiles&diff=1143Format of Spectral Multifiles2026-03-09T10:00:22Z<p>Laschp: /* Quality test results - spec.qt */</p>
<hr />
<div>Spectra multifiles combine metadata and spectral data from multiple mass spectra in one single file. Such multifiles files are stored in a Matlab&trade; specific format, structure arrays, that contain different files for spectral data as well as metadata. Spectra multifiles can be loaded in the Matlab environment by entering the following command at the Matlab command prompt:<br />
<br />
>> load('muffname','-mat');<br />
<br />
where ''muffname'' denotes the name of the spectrum multifile. For example, the command ''load('RKI-ring-trial-spectra.muf','-mat')'' will open the file ''RKI-ring-trial-spectra.muf'', a MALDI-ToF mass spectrum multifile containing 24 individual MALDI-ToF mass spectra acquired within the ''so called'' [https://pubmed.ncbi.nlm.nih.gov/26063856/ '''RKI ring trial study''']. The file ''RKI-ring-trial-spectra.muf'' can be downloaded [https://wiki.microbe-ms.com/upload/RKI-ring-trial-spectra.muf: '''here''']. If loading was successful, you will have access to a new Matlab variable ''spec'' (struc array). Details of the structure of ''spec'' are described next.<br> &nbsp; <br><br />
<br />
== Fields of the structure array - '''''spec''''' ==<br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Data type<br />
!width=300|<br />
|-<br />
| org<br />
| original mass spectra [2 x n array], n: number of data points<br />
| float32<br />
| rowspan="41" style="background: #ffffff;" valign="top" | [[File:Multifile-format-spec-struc.png|250px|thumb|center|Screenshot showing the content of the structure array ''spec'' that is stored in ''so called'' spectrum multi files (*.muf). Fields of ''spec'' contain spectral data (original, i.e. unmodified, and pre-processed), spectrum metadata as well as peak lists, calibration information, results of quality tests, and information collected during creation of average, or database spectra. In the example of the given screenshot, the content of one database spectrum is depicted.]]<br />
|-<br />
| pre<br />
| pre-processed spectra [2 x n array], n: number of data points<br />
| float32<br />
|-<br />
| nam<br />
| spectra id<br />
| char array<br />
|-<br />
| gen<br />
| genus information<br />
| char array<br />
|-<br />
| spe<br />
| species info<br />
| char array<br />
|-<br />
| str<br />
| strain info<br />
| char array<br />
|-<br />
| typ<br />
| type<br />
| char array<br />
|-<br />
| uid<br />
| taxonomy identification number for species as used by the NCBI (see [https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi]), can be modified<br />
| char array<br />
|-<br />
| uie<br />
| unmodified taxonomy identification number for strains used by the NCBI (see [https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi])<br />
| char array<br />
|-<br />
| gti<br />
| cultivation conditions: growth time<br />
| char array<br />
|-<br />
| tem<br />
| cultivation conditions: cultivation temperature<br />
| char array<br />
|-<br />
| air<br />
| cultivation conditions: cultivation under aerobic or anaerobic conditions<br />
| char array<br />
|-<br />
| med<br />
| cultivation conditions: cultivation medium<br />
| char array<br />
|-<br />
| spo<br />
| spore formers (Yes or No)<br />
| char array<br />
|-<br />
| con<br />
| sample concentration<br />
| char array<br />
|-<br />
| trt <br />
| sample treatment<br />
| char array<br />
|-<br />
| ext <br />
| extra information<br />
| char array<br />
|-<br />
| las <br />
| laser parameters (power, spot diameter, frequency, etc.)<br />
| char array<br />
|-<br />
| cal <br />
| calibration info<br />
| char array<br />
|-<br />
| met<br />
| measurement method<br />
| char array<br />
|-<br />
| cus <br />
| customer info<br />
| char array<br />
|-<br />
| tim <br />
| date and time of measurement<br />
| char array<br />
|-<br />
| pth<br />
| path to spectrum<br />
| char array<br />
|-<br />
| cls<br />
| class assignment (valid values are 0,1,2,3 and 4)<br />
| float32<br />
|-<br />
| lst<br />
| formatted text containing the peak table info<br />
| char array<br />
|-<br />
| seq<br />
| sequence of pre-processing steps<br />
| char array<br />
|-<br />
| smo<br />
| the number of smoothing points (Savitzky-Golay smoothing)<br />
| char array<br />
|-<br />
| bas<br />
| number of intervals used for baseline correction<br />
| float32<br />
|-<br />
| nrm<br />
| normalization parameter (Yes:1, No:0)<br />
| float32<br />
|-<br />
| clb<br />
| calibration parameters (not used)<br />
| float32<br />
|-<br />
| red<br />
| data reduction factor (spectral binning)<br />
| char array<br />
|-<br />
| cut<br />
| cut in the spectral domain, m/z range<br />
| char array<br />
|-<br />
| tmp<br />
| temporary info (not always present)<br />
| char array<br />
|-<br />
| mod<br />
| original data modified by cut spectra or reduce resolution (Yes:1, No:0)<br />
| float32<br />
|-<br />
| lms<br />
| MALDI-ToF MS, or LC-MS&sup1; data? (0: MALDI, 1: LC-MS&sup1;)<br />
| float32<br />
|-<br />
| pik<br />
| [[#peak table format|peak table]], an array of the dimension [4 x npeaks] or [6 x npeaks], where npeaks denotes the number of peaks <br />
| float 32<br />
|-<br />
| ccl<br />
| [[#structure array ccl|calibration information]]<br />
| struc array<br />
|-<br />
| avr<br />
| [[#structure array avr|average spectrum]]<br />
| struc array<br />
|-<br />
| dbs<br />
| [[#structure array dbs|data base spectrum]]<br />
| struc array<br />
|-<br />
| prm<br />
| parameters of peak detection<br />
| char array<br />
|-<br />
| qt<br />
| quality test parameter<br />
| struc array<br />
|-<br />
|}<br />
<br />
== Peak table format - '''''spec.pik''''' ==<br />
<br />
<span class="mw-headline" id="peak table format"></span><br />
<br><br />
{| class="wikitable" width=800<br />
!width=100| Fields<br />
!width=700| Description<br />
|-<br />
| spec.pik(1,:) <br> &nbsp; <br><br />
| m/z positions of the peaks in the peak table <br> &nbsp; <br> <br />
|-<br />
| spec.pik(2,:) <br> &nbsp; <br><br />
| absolute intensities of these peaks <br> &nbsp; <br><br />
|-<br />
| spec.pik(3,:) <br> &nbsp; <br><br />
| weighting factors (the sum of these factors equals 100) <br> &nbsp; <br><br />
|-<br />
| spec.pik(4,:) <br> &nbsp; <br><br />
| in case of single spectra, i.e. no database or average spectra: baseline-corrected absolute intensities of the peaks, in case of average or database spectra: the relative peak frequency<br />
|-<br />
| spec.pik(5,:) <br> &nbsp; <br><br />
| FWHH of the given peak (requires QT) <br> &nbsp; <br><br />
|-<br />
| spec.pik(6,:) <br> &nbsp; <br><br />
| resolving power of the given peak (requires QT) <br> &nbsp; <br><br />
|}<br />
<br />
<br />
== Calibration information - '''''spec.ccl''''' ==<br />
<br />
<span class="mw-headline" id="structure array ccl"></span><br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| cl1<br />
| calibration constant 1<br />
| float32<br />
| rowspan="15" style="background: #ffffff;" valign="top" | [[File:calibration-format-spec-struc.png|250px|thumb|center|Screenshot showing the content of the structure array spec.ccl containing the calibration info (calibration constants, delay time, number of spectrum data points, etc.)]]<br />
|-<br />
| cl2<br />
| calibration constant 2<br />
| float32<br />
|-<br />
| cl3<br />
| calibration constant 3<br />
| float32<br />
|-<br />
| del <br />
| delay time [ns]<br />
| float32<br />
|-<br />
| npt<br />
| number of data points<br />
| float32<br />
|-<br />
| res <br />
| time resolution [ns]<br />
| float32<br />
|-<br />
| ncl<br />
| calibration info required to store the spectrum in a Bruker-specific data format <br />
| char array<br />
|-<br />
| ncr<br />
| calibration info required to store the spectrum in a Bruker-specific data format <br />
| char array<br />
|-<br />
| bid<br />
| hardware id of the spectrum ('Bruker ID')<br />
| char array<br />
|-<br />
| mid<br />
| MicrobeMS id of the spectrum<br />
| char array<br />
|-<br />
| org<br />
| manufacturer info<br />
| char array<br />
|-<br />
| tfu<br />
| 'ToF user'<br />
| char array<br />
|-<br />
| spm<br />
| not used<br />
| char array<br />
|-<br />
| stp<br />
| type of measurement (should be 'TOF')<br />
| char array<br />
|-<br />
| acq<br />
| further acquisition info<br />
| char array<br />
|}<br />
<br />
<br />
== Database spectra - '''''spec.dbs''''' ==<br />
<br />
<span class="mw-headline" id="structure array dbs"></span><br />
<br><br />
A [[Create database spectra|database spectrum]] is usually created from many (>3) individual mass spectra. Like in regular experimental spectra, spectral data and metadata of average spectra are stored in specific fields of structure array ''spec''. In database spectra the field ''spec(i).dbs'' is used to store relevant data from experimental source spectra from which the given database spectrum has been derived. These fields are left empty in experimental and average spectra. Details of the structure of ''spec.dbs'' are given in the table below. <br />
<br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| mem<br />
| specifies whether the current spectrum is a data base spectrum (1) or not (0)<br />
| char array<br />
| rowspan="5" style="background: #ffffff;" valign="top" |[[File:dbs-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''spec.dbs''. This screenshot shows information like the spectrum id, taxonomic information, peak tables, respective peak detection parameters, etc of mass spectrum #1 [spec(1).dbs(1,1)] that was used with others to obtain a database spectrum]]<br />
|-<br />
| ids<br />
| ID's of the individual mass spectra that contributed to the given database spectrum<br />
| char array<br />
|-<br />
| tax<br />
| contains taxonomical information (i.e. the genus, species, strain information)<br />
| char array<br />
|-<br />
| pik<br />
| peak table of the given source spectrum <br />
| float32<br />
|-<br />
| prm<br />
| parameters used for peak detection <br />
| char array<br />
|}<br />
<br />
== Average spectra - '''''spec.avr''''' ==<br />
<br />
<span class="mw-headline" id="structure array avr"></span><br />
<br><br />
An [[Averaging Mass Spectra|average spectrum]] is usually created from many (>3) individual mass spectra. Like in regular experimental spectra, spectral data and metadata of average spectra are stored in specific fields of structure array ''spec''. In average spectra the field ''spec(i).avr'' is used to store relevant data from experimental source spectra from which the given average spectrum has been derived. These fields are empty in experimental and database spectra. Details of the structure of ''spec.avr'' are given in the table below. <br />
<br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| mem<br />
| specifies whether the contributing spectrum is an average spectrum (1) or not (0)<br />
| char array<br />
| rowspan="6" style="background: #ffffff;" valign="top" |[[File:avr-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''spec.avr''. This screenshot shows information like the spectrum id, taxonomic information, peak tables, respective peak detection parameters, etc of mass spectrum #1 [spec(1).avr(1,1)] that was used with others to obtain an average spectrum]]<br />
|-<br />
| ids<br />
| ID's of the individual mass spectra that contributed to the given average spectrum<br />
| char array<br />
|-<br />
| tax<br />
| contains taxonomical information (i.e. the genus, species, strain information)<br />
| char array<br />
|-<br />
| pik<br />
| peak table of the given source spectrum <br />
| float32<br />
|-<br />
| prm<br />
| parameters used for peak detection <br />
| char array<br />
|}<br />
<br />
== Quality test results - '''''spec.qt''''' ==<br />
<br />
<span class="mw-headline" id="structure array qt"></span><br />
<br><br />
The structure array ''spec.qt'' contains the results of a [[MALDI Quality Tests|Quality Test]]. Fields of this structure are empty if no QT has been performed. Details of the structure of ''spec.qt'' are given in the table below. <br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| noise<br />
| QT data of the ''noise'' test, contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
| rowspan="7" style="background: #ffffff;" valign="top" |[[File:qt-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''spec.qt'' that contains the results of a quality test (QT).]]<br />
|-<br />
| basln<br />
| QT data of the ''baseline'' test, contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| npiks<br />
| QT data of the test ''number of peaks'', contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| respw<br />
| QT data of the test ''resolution power'', contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| rnk<br />
| overall rank the given spectrum has achieved in a QT with a number of other spectra<br />
| float32<br />
|-<br />
| res<br />
| overall quality test score<br />
| float32<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Format_of_Spectral_Multifiles&diff=1142Format of Spectral Multifiles2026-03-09T09:58:29Z<p>Laschp: /* Average spectra - spec.avr */</p>
<hr />
<div>Spectra multifiles combine metadata and spectral data from multiple mass spectra in one single file. Such multifiles files are stored in a Matlab&trade; specific format, structure arrays, that contain different files for spectral data as well as metadata. Spectra multifiles can be loaded in the Matlab environment by entering the following command at the Matlab command prompt:<br />
<br />
>> load('muffname','-mat');<br />
<br />
where ''muffname'' denotes the name of the spectrum multifile. For example, the command ''load('RKI-ring-trial-spectra.muf','-mat')'' will open the file ''RKI-ring-trial-spectra.muf'', a MALDI-ToF mass spectrum multifile containing 24 individual MALDI-ToF mass spectra acquired within the ''so called'' [https://pubmed.ncbi.nlm.nih.gov/26063856/ '''RKI ring trial study''']. The file ''RKI-ring-trial-spectra.muf'' can be downloaded [https://wiki.microbe-ms.com/upload/RKI-ring-trial-spectra.muf: '''here''']. If loading was successful, you will have access to a new Matlab variable ''spec'' (struc array). Details of the structure of ''spec'' are described next.<br> &nbsp; <br><br />
<br />
== Fields of the structure array - '''''spec''''' ==<br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Data type<br />
!width=300|<br />
|-<br />
| org<br />
| original mass spectra [2 x n array], n: number of data points<br />
| float32<br />
| rowspan="41" style="background: #ffffff;" valign="top" | [[File:Multifile-format-spec-struc.png|250px|thumb|center|Screenshot showing the content of the structure array ''spec'' that is stored in ''so called'' spectrum multi files (*.muf). Fields of ''spec'' contain spectral data (original, i.e. unmodified, and pre-processed), spectrum metadata as well as peak lists, calibration information, results of quality tests, and information collected during creation of average, or database spectra. In the example of the given screenshot, the content of one database spectrum is depicted.]]<br />
|-<br />
| pre<br />
| pre-processed spectra [2 x n array], n: number of data points<br />
| float32<br />
|-<br />
| nam<br />
| spectra id<br />
| char array<br />
|-<br />
| gen<br />
| genus information<br />
| char array<br />
|-<br />
| spe<br />
| species info<br />
| char array<br />
|-<br />
| str<br />
| strain info<br />
| char array<br />
|-<br />
| typ<br />
| type<br />
| char array<br />
|-<br />
| uid<br />
| taxonomy identification number for species as used by the NCBI (see [https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi]), can be modified<br />
| char array<br />
|-<br />
| uie<br />
| unmodified taxonomy identification number for strains used by the NCBI (see [https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi])<br />
| char array<br />
|-<br />
| gti<br />
| cultivation conditions: growth time<br />
| char array<br />
|-<br />
| tem<br />
| cultivation conditions: cultivation temperature<br />
| char array<br />
|-<br />
| air<br />
| cultivation conditions: cultivation under aerobic or anaerobic conditions<br />
| char array<br />
|-<br />
| med<br />
| cultivation conditions: cultivation medium<br />
| char array<br />
|-<br />
| spo<br />
| spore formers (Yes or No)<br />
| char array<br />
|-<br />
| con<br />
| sample concentration<br />
| char array<br />
|-<br />
| trt <br />
| sample treatment<br />
| char array<br />
|-<br />
| ext <br />
| extra information<br />
| char array<br />
|-<br />
| las <br />
| laser parameters (power, spot diameter, frequency, etc.)<br />
| char array<br />
|-<br />
| cal <br />
| calibration info<br />
| char array<br />
|-<br />
| met<br />
| measurement method<br />
| char array<br />
|-<br />
| cus <br />
| customer info<br />
| char array<br />
|-<br />
| tim <br />
| date and time of measurement<br />
| char array<br />
|-<br />
| pth<br />
| path to spectrum<br />
| char array<br />
|-<br />
| cls<br />
| class assignment (valid values are 0,1,2,3 and 4)<br />
| float32<br />
|-<br />
| lst<br />
| formatted text containing the peak table info<br />
| char array<br />
|-<br />
| seq<br />
| sequence of pre-processing steps<br />
| char array<br />
|-<br />
| smo<br />
| the number of smoothing points (Savitzky-Golay smoothing)<br />
| char array<br />
|-<br />
| bas<br />
| number of intervals used for baseline correction<br />
| float32<br />
|-<br />
| nrm<br />
| normalization parameter (Yes:1, No:0)<br />
| float32<br />
|-<br />
| clb<br />
| calibration parameters (not used)<br />
| float32<br />
|-<br />
| red<br />
| data reduction factor (spectral binning)<br />
| char array<br />
|-<br />
| cut<br />
| cut in the spectral domain, m/z range<br />
| char array<br />
|-<br />
| tmp<br />
| temporary info (not always present)<br />
| char array<br />
|-<br />
| mod<br />
| original data modified by cut spectra or reduce resolution (Yes:1, No:0)<br />
| float32<br />
|-<br />
| lms<br />
| MALDI-ToF MS, or LC-MS&sup1; data? (0: MALDI, 1: LC-MS&sup1;)<br />
| float32<br />
|-<br />
| pik<br />
| [[#peak table format|peak table]], an array of the dimension [4 x npeaks] or [6 x npeaks], where npeaks denotes the number of peaks <br />
| float 32<br />
|-<br />
| ccl<br />
| [[#structure array ccl|calibration information]]<br />
| struc array<br />
|-<br />
| avr<br />
| [[#structure array avr|average spectrum]]<br />
| struc array<br />
|-<br />
| dbs<br />
| [[#structure array dbs|data base spectrum]]<br />
| struc array<br />
|-<br />
| prm<br />
| parameters of peak detection<br />
| char array<br />
|-<br />
| qt<br />
| quality test parameter<br />
| struc array<br />
|-<br />
|}<br />
<br />
== Peak table format - '''''spec.pik''''' ==<br />
<br />
<span class="mw-headline" id="peak table format"></span><br />
<br><br />
{| class="wikitable" width=800<br />
!width=100| Fields<br />
!width=700| Description<br />
|-<br />
| spec.pik(1,:) <br> &nbsp; <br><br />
| m/z positions of the peaks in the peak table <br> &nbsp; <br> <br />
|-<br />
| spec.pik(2,:) <br> &nbsp; <br><br />
| absolute intensities of these peaks <br> &nbsp; <br><br />
|-<br />
| spec.pik(3,:) <br> &nbsp; <br><br />
| weighting factors (the sum of these factors equals 100) <br> &nbsp; <br><br />
|-<br />
| spec.pik(4,:) <br> &nbsp; <br><br />
| in case of single spectra, i.e. no database or average spectra: baseline-corrected absolute intensities of the peaks, in case of average or database spectra: the relative peak frequency<br />
|-<br />
| spec.pik(5,:) <br> &nbsp; <br><br />
| FWHH of the given peak (requires QT) <br> &nbsp; <br><br />
|-<br />
| spec.pik(6,:) <br> &nbsp; <br><br />
| resolving power of the given peak (requires QT) <br> &nbsp; <br><br />
|}<br />
<br />
<br />
== Calibration information - '''''spec.ccl''''' ==<br />
<br />
<span class="mw-headline" id="structure array ccl"></span><br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| cl1<br />
| calibration constant 1<br />
| float32<br />
| rowspan="15" style="background: #ffffff;" valign="top" | [[File:calibration-format-spec-struc.png|250px|thumb|center|Screenshot showing the content of the structure array spec.ccl containing the calibration info (calibration constants, delay time, number of spectrum data points, etc.)]]<br />
|-<br />
| cl2<br />
| calibration constant 2<br />
| float32<br />
|-<br />
| cl3<br />
| calibration constant 3<br />
| float32<br />
|-<br />
| del <br />
| delay time [ns]<br />
| float32<br />
|-<br />
| npt<br />
| number of data points<br />
| float32<br />
|-<br />
| res <br />
| time resolution [ns]<br />
| float32<br />
|-<br />
| ncl<br />
| calibration info required to store the spectrum in a Bruker-specific data format <br />
| char array<br />
|-<br />
| ncr<br />
| calibration info required to store the spectrum in a Bruker-specific data format <br />
| char array<br />
|-<br />
| bid<br />
| hardware id of the spectrum ('Bruker ID')<br />
| char array<br />
|-<br />
| mid<br />
| MicrobeMS id of the spectrum<br />
| char array<br />
|-<br />
| org<br />
| manufacturer info<br />
| char array<br />
|-<br />
| tfu<br />
| 'ToF user'<br />
| char array<br />
|-<br />
| spm<br />
| not used<br />
| char array<br />
|-<br />
| stp<br />
| type of measurement (should be 'TOF')<br />
| char array<br />
|-<br />
| acq<br />
| further acquisition info<br />
| char array<br />
|}<br />
<br />
<br />
== Database spectra - '''''spec.dbs''''' ==<br />
<br />
<span class="mw-headline" id="structure array dbs"></span><br />
<br><br />
A [[Create database spectra|database spectrum]] is usually created from many (>3) individual mass spectra. Like in regular experimental spectra, spectral data and metadata of average spectra are stored in specific fields of structure array ''spec''. In database spectra the field ''spec(i).dbs'' is used to store relevant data from experimental source spectra from which the given database spectrum has been derived. These fields are left empty in experimental and average spectra. Details of the structure of ''spec.dbs'' are given in the table below. <br />
<br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| mem<br />
| specifies whether the current spectrum is a data base spectrum (1) or not (0)<br />
| char array<br />
| rowspan="5" style="background: #ffffff;" valign="top" |[[File:dbs-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''spec.dbs''. This screenshot shows information like the spectrum id, taxonomic information, peak tables, respective peak detection parameters, etc of mass spectrum #1 [spec(1).dbs(1,1)] that was used with others to obtain a database spectrum]]<br />
|-<br />
| ids<br />
| ID's of the individual mass spectra that contributed to the given database spectrum<br />
| char array<br />
|-<br />
| tax<br />
| contains taxonomical information (i.e. the genus, species, strain information)<br />
| char array<br />
|-<br />
| pik<br />
| peak table of the given source spectrum <br />
| float32<br />
|-<br />
| prm<br />
| parameters used for peak detection <br />
| char array<br />
|}<br />
<br />
== Average spectra - '''''spec.avr''''' ==<br />
<br />
<span class="mw-headline" id="structure array avr"></span><br />
<br><br />
An [[Averaging Mass Spectra|average spectrum]] is usually created from many (>3) individual mass spectra. Like in regular experimental spectra, spectral data and metadata of average spectra are stored in specific fields of structure array ''spec''. In average spectra the field ''spec(i).avr'' is used to store relevant data from experimental source spectra from which the given average spectrum has been derived. These fields are empty in experimental and database spectra. Details of the structure of ''spec.avr'' are given in the table below. <br />
<br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| mem<br />
| specifies whether the contributing spectrum is an average spectrum (1) or not (0)<br />
| char array<br />
| rowspan="6" style="background: #ffffff;" valign="top" |[[File:avr-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''spec.avr''. This screenshot shows information like the spectrum id, taxonomic information, peak tables, respective peak detection parameters, etc of mass spectrum #1 [spec(1).avr(1,1)] that was used with others to obtain an average spectrum]]<br />
|-<br />
| ids<br />
| ID's of the individual mass spectra that contributed to the given average spectrum<br />
| char array<br />
|-<br />
| tax<br />
| contains taxonomical information (i.e. the genus, species, strain information)<br />
| char array<br />
|-<br />
| pik<br />
| peak table of the given source spectrum <br />
| float32<br />
|-<br />
| prm<br />
| parameters used for peak detection <br />
| char array<br />
|}<br />
<br />
== Quality test results - '''''spec.qt''''' ==<br />
<br />
<span class="mw-headline" id="structure array qt"></span><br />
<br><br />
The structure array ''spec.qt'' contains the results of a [[MALDI Quality Tests|Quality Test]]. Fields of this structure are empty if no QT has been performed. Details of the structure of ''spec.qt'' are given in the table below. <br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| noise<br />
| QT data of the ''noise'' test, contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
| rowspan="7" style="background: #ffffff;" valign="top" |[[File:qt-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''spec.qt'' that contains the results of a quality test (QT).]]<br />
|-<br />
| basln<br />
| QT data of the ''baseline'' test, contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| npiks<br />
| QT data of the test ''number of peaks'', contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| respw<br />
| QT data of the test ''resolution power'', contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| rnk<br />
| overall rank that the given spectrum has achieved in a QT with a number of other spectra<br />
| float32<br />
|-<br />
| res<br />
| overall quality test score<br />
| float32<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Format_of_Spectral_Multifiles&diff=1141Format of Spectral Multifiles2026-03-09T09:58:04Z<p>Laschp: /* Database spectra - spec.dbs */</p>
<hr />
<div>Spectra multifiles combine metadata and spectral data from multiple mass spectra in one single file. Such multifiles files are stored in a Matlab&trade; specific format, structure arrays, that contain different files for spectral data as well as metadata. Spectra multifiles can be loaded in the Matlab environment by entering the following command at the Matlab command prompt:<br />
<br />
>> load('muffname','-mat');<br />
<br />
where ''muffname'' denotes the name of the spectrum multifile. For example, the command ''load('RKI-ring-trial-spectra.muf','-mat')'' will open the file ''RKI-ring-trial-spectra.muf'', a MALDI-ToF mass spectrum multifile containing 24 individual MALDI-ToF mass spectra acquired within the ''so called'' [https://pubmed.ncbi.nlm.nih.gov/26063856/ '''RKI ring trial study''']. The file ''RKI-ring-trial-spectra.muf'' can be downloaded [https://wiki.microbe-ms.com/upload/RKI-ring-trial-spectra.muf: '''here''']. If loading was successful, you will have access to a new Matlab variable ''spec'' (struc array). Details of the structure of ''spec'' are described next.<br> &nbsp; <br><br />
<br />
== Fields of the structure array - '''''spec''''' ==<br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Data type<br />
!width=300|<br />
|-<br />
| org<br />
| original mass spectra [2 x n array], n: number of data points<br />
| float32<br />
| rowspan="41" style="background: #ffffff;" valign="top" | [[File:Multifile-format-spec-struc.png|250px|thumb|center|Screenshot showing the content of the structure array ''spec'' that is stored in ''so called'' spectrum multi files (*.muf). Fields of ''spec'' contain spectral data (original, i.e. unmodified, and pre-processed), spectrum metadata as well as peak lists, calibration information, results of quality tests, and information collected during creation of average, or database spectra. In the example of the given screenshot, the content of one database spectrum is depicted.]]<br />
|-<br />
| pre<br />
| pre-processed spectra [2 x n array], n: number of data points<br />
| float32<br />
|-<br />
| nam<br />
| spectra id<br />
| char array<br />
|-<br />
| gen<br />
| genus information<br />
| char array<br />
|-<br />
| spe<br />
| species info<br />
| char array<br />
|-<br />
| str<br />
| strain info<br />
| char array<br />
|-<br />
| typ<br />
| type<br />
| char array<br />
|-<br />
| uid<br />
| taxonomy identification number for species as used by the NCBI (see [https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi]), can be modified<br />
| char array<br />
|-<br />
| uie<br />
| unmodified taxonomy identification number for strains used by the NCBI (see [https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi])<br />
| char array<br />
|-<br />
| gti<br />
| cultivation conditions: growth time<br />
| char array<br />
|-<br />
| tem<br />
| cultivation conditions: cultivation temperature<br />
| char array<br />
|-<br />
| air<br />
| cultivation conditions: cultivation under aerobic or anaerobic conditions<br />
| char array<br />
|-<br />
| med<br />
| cultivation conditions: cultivation medium<br />
| char array<br />
|-<br />
| spo<br />
| spore formers (Yes or No)<br />
| char array<br />
|-<br />
| con<br />
| sample concentration<br />
| char array<br />
|-<br />
| trt <br />
| sample treatment<br />
| char array<br />
|-<br />
| ext <br />
| extra information<br />
| char array<br />
|-<br />
| las <br />
| laser parameters (power, spot diameter, frequency, etc.)<br />
| char array<br />
|-<br />
| cal <br />
| calibration info<br />
| char array<br />
|-<br />
| met<br />
| measurement method<br />
| char array<br />
|-<br />
| cus <br />
| customer info<br />
| char array<br />
|-<br />
| tim <br />
| date and time of measurement<br />
| char array<br />
|-<br />
| pth<br />
| path to spectrum<br />
| char array<br />
|-<br />
| cls<br />
| class assignment (valid values are 0,1,2,3 and 4)<br />
| float32<br />
|-<br />
| lst<br />
| formatted text containing the peak table info<br />
| char array<br />
|-<br />
| seq<br />
| sequence of pre-processing steps<br />
| char array<br />
|-<br />
| smo<br />
| the number of smoothing points (Savitzky-Golay smoothing)<br />
| char array<br />
|-<br />
| bas<br />
| number of intervals used for baseline correction<br />
| float32<br />
|-<br />
| nrm<br />
| normalization parameter (Yes:1, No:0)<br />
| float32<br />
|-<br />
| clb<br />
| calibration parameters (not used)<br />
| float32<br />
|-<br />
| red<br />
| data reduction factor (spectral binning)<br />
| char array<br />
|-<br />
| cut<br />
| cut in the spectral domain, m/z range<br />
| char array<br />
|-<br />
| tmp<br />
| temporary info (not always present)<br />
| char array<br />
|-<br />
| mod<br />
| original data modified by cut spectra or reduce resolution (Yes:1, No:0)<br />
| float32<br />
|-<br />
| lms<br />
| MALDI-ToF MS, or LC-MS&sup1; data? (0: MALDI, 1: LC-MS&sup1;)<br />
| float32<br />
|-<br />
| pik<br />
| [[#peak table format|peak table]], an array of the dimension [4 x npeaks] or [6 x npeaks], where npeaks denotes the number of peaks <br />
| float 32<br />
|-<br />
| ccl<br />
| [[#structure array ccl|calibration information]]<br />
| struc array<br />
|-<br />
| avr<br />
| [[#structure array avr|average spectrum]]<br />
| struc array<br />
|-<br />
| dbs<br />
| [[#structure array dbs|data base spectrum]]<br />
| struc array<br />
|-<br />
| prm<br />
| parameters of peak detection<br />
| char array<br />
|-<br />
| qt<br />
| quality test parameter<br />
| struc array<br />
|-<br />
|}<br />
<br />
== Peak table format - '''''spec.pik''''' ==<br />
<br />
<span class="mw-headline" id="peak table format"></span><br />
<br><br />
{| class="wikitable" width=800<br />
!width=100| Fields<br />
!width=700| Description<br />
|-<br />
| spec.pik(1,:) <br> &nbsp; <br><br />
| m/z positions of the peaks in the peak table <br> &nbsp; <br> <br />
|-<br />
| spec.pik(2,:) <br> &nbsp; <br><br />
| absolute intensities of these peaks <br> &nbsp; <br><br />
|-<br />
| spec.pik(3,:) <br> &nbsp; <br><br />
| weighting factors (the sum of these factors equals 100) <br> &nbsp; <br><br />
|-<br />
| spec.pik(4,:) <br> &nbsp; <br><br />
| in case of single spectra, i.e. no database or average spectra: baseline-corrected absolute intensities of the peaks, in case of average or database spectra: the relative peak frequency<br />
|-<br />
| spec.pik(5,:) <br> &nbsp; <br><br />
| FWHH of the given peak (requires QT) <br> &nbsp; <br><br />
|-<br />
| spec.pik(6,:) <br> &nbsp; <br><br />
| resolving power of the given peak (requires QT) <br> &nbsp; <br><br />
|}<br />
<br />
<br />
== Calibration information - '''''spec.ccl''''' ==<br />
<br />
<span class="mw-headline" id="structure array ccl"></span><br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| cl1<br />
| calibration constant 1<br />
| float32<br />
| rowspan="15" style="background: #ffffff;" valign="top" | [[File:calibration-format-spec-struc.png|250px|thumb|center|Screenshot showing the content of the structure array spec.ccl containing the calibration info (calibration constants, delay time, number of spectrum data points, etc.)]]<br />
|-<br />
| cl2<br />
| calibration constant 2<br />
| float32<br />
|-<br />
| cl3<br />
| calibration constant 3<br />
| float32<br />
|-<br />
| del <br />
| delay time [ns]<br />
| float32<br />
|-<br />
| npt<br />
| number of data points<br />
| float32<br />
|-<br />
| res <br />
| time resolution [ns]<br />
| float32<br />
|-<br />
| ncl<br />
| calibration info required to store the spectrum in a Bruker-specific data format <br />
| char array<br />
|-<br />
| ncr<br />
| calibration info required to store the spectrum in a Bruker-specific data format <br />
| char array<br />
|-<br />
| bid<br />
| hardware id of the spectrum ('Bruker ID')<br />
| char array<br />
|-<br />
| mid<br />
| MicrobeMS id of the spectrum<br />
| char array<br />
|-<br />
| org<br />
| manufacturer info<br />
| char array<br />
|-<br />
| tfu<br />
| 'ToF user'<br />
| char array<br />
|-<br />
| spm<br />
| not used<br />
| char array<br />
|-<br />
| stp<br />
| type of measurement (should be 'TOF')<br />
| char array<br />
|-<br />
| acq<br />
| further acquisition info<br />
| char array<br />
|}<br />
<br />
<br />
== Database spectra - '''''spec.dbs''''' ==<br />
<br />
<span class="mw-headline" id="structure array dbs"></span><br />
<br><br />
A [[Create database spectra|database spectrum]] is usually created from many (>3) individual mass spectra. Like in regular experimental spectra, spectral data and metadata of average spectra are stored in specific fields of structure array ''spec''. In database spectra the field ''spec(i).dbs'' is used to store relevant data from experimental source spectra from which the given database spectrum has been derived. These fields are left empty in experimental and average spectra. Details of the structure of ''spec.dbs'' are given in the table below. <br />
<br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| mem<br />
| specifies whether the current spectrum is a data base spectrum (1) or not (0)<br />
| char array<br />
| rowspan="5" style="background: #ffffff;" valign="top" |[[File:dbs-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''spec.dbs''. This screenshot shows information like the spectrum id, taxonomic information, peak tables, respective peak detection parameters, etc of mass spectrum #1 [spec(1).dbs(1,1)] that was used with others to obtain a database spectrum]]<br />
|-<br />
| ids<br />
| ID's of the individual mass spectra that contributed to the given database spectrum<br />
| char array<br />
|-<br />
| tax<br />
| contains taxonomical information (i.e. the genus, species, strain information)<br />
| char array<br />
|-<br />
| pik<br />
| peak table of the given source spectrum <br />
| float32<br />
|-<br />
| prm<br />
| parameters used for peak detection <br />
| char array<br />
|}<br />
<br />
== Average spectra - '''''spec.avr''''' ==<br />
<br />
<span class="mw-headline" id="structure array avr"></span><br />
<br><br />
An [[Averaging Mass Spectra|average spectrum]] is usually created from many (>3) individual mass spectra. Like in regular experimental spectra, spectral data and metadata of average spectra are stored in specific fields of structure array ''spec''. In average spectra the field ''spec(i).avr'' is used to store relevant data from experimental source spectra from which the given average spectrum has been derived. These fields are empty in experimental and database spectra. Details of the structure of ''spec.avr'' are given in the table below. <br />
<br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| mem<br />
| specifies whether the contributing spectrum is an average spectrum (1) or not (0)<br />
| char array<br />
| rowspan="6" style="background: #ffffff;" valign="top" |[[File:avr-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''spec.avr''. This screenshot shows information like the spectrum id, taxonomic information, peak tables, respective peak detection parameters, etc of mass spectrum #1 [spec(1).avr(1,1)] that was used with others to obtain an average spectrum]]<br />
|-<br />
| ids<br />
| id of the individual mass spectrum that contributed to the given average spectrum<br />
| char array<br />
|-<br />
| tax<br />
| contains taxonomical information (i.e. the genus, species, strain information)<br />
| char array<br />
|-<br />
| pik<br />
| peak table of the given source spectrum <br />
| float32<br />
|-<br />
| prm<br />
| parameters used for peak detection <br />
| char array<br />
|}<br />
<br />
<br />
== Quality test results - '''''spec.qt''''' ==<br />
<br />
<span class="mw-headline" id="structure array qt"></span><br />
<br><br />
The structure array ''spec.qt'' contains the results of a [[MALDI Quality Tests|Quality Test]]. Fields of this structure are empty if no QT has been performed. Details of the structure of ''spec.qt'' are given in the table below. <br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| noise<br />
| QT data of the ''noise'' test, contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
| rowspan="7" style="background: #ffffff;" valign="top" |[[File:qt-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''spec.qt'' that contains the results of a quality test (QT).]]<br />
|-<br />
| basln<br />
| QT data of the ''baseline'' test, contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| npiks<br />
| QT data of the test ''number of peaks'', contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| respw<br />
| QT data of the test ''resolution power'', contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| rnk<br />
| overall rank that the given spectrum has achieved in a QT with a number of other spectra<br />
| float32<br />
|-<br />
| res<br />
| overall quality test score<br />
| float32<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Format_of_Spectral_Multifiles&diff=1140Format of Spectral Multifiles2026-03-09T09:57:47Z<p>Laschp: /* Database spectra - spec.dbs */</p>
<hr />
<div>Spectra multifiles combine metadata and spectral data from multiple mass spectra in one single file. Such multifiles files are stored in a Matlab&trade; specific format, structure arrays, that contain different files for spectral data as well as metadata. Spectra multifiles can be loaded in the Matlab environment by entering the following command at the Matlab command prompt:<br />
<br />
>> load('muffname','-mat');<br />
<br />
where ''muffname'' denotes the name of the spectrum multifile. For example, the command ''load('RKI-ring-trial-spectra.muf','-mat')'' will open the file ''RKI-ring-trial-spectra.muf'', a MALDI-ToF mass spectrum multifile containing 24 individual MALDI-ToF mass spectra acquired within the ''so called'' [https://pubmed.ncbi.nlm.nih.gov/26063856/ '''RKI ring trial study''']. The file ''RKI-ring-trial-spectra.muf'' can be downloaded [https://wiki.microbe-ms.com/upload/RKI-ring-trial-spectra.muf: '''here''']. If loading was successful, you will have access to a new Matlab variable ''spec'' (struc array). Details of the structure of ''spec'' are described next.<br> &nbsp; <br><br />
<br />
== Fields of the structure array - '''''spec''''' ==<br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Data type<br />
!width=300|<br />
|-<br />
| org<br />
| original mass spectra [2 x n array], n: number of data points<br />
| float32<br />
| rowspan="41" style="background: #ffffff;" valign="top" | [[File:Multifile-format-spec-struc.png|250px|thumb|center|Screenshot showing the content of the structure array ''spec'' that is stored in ''so called'' spectrum multi files (*.muf). Fields of ''spec'' contain spectral data (original, i.e. unmodified, and pre-processed), spectrum metadata as well as peak lists, calibration information, results of quality tests, and information collected during creation of average, or database spectra. In the example of the given screenshot, the content of one database spectrum is depicted.]]<br />
|-<br />
| pre<br />
| pre-processed spectra [2 x n array], n: number of data points<br />
| float32<br />
|-<br />
| nam<br />
| spectra id<br />
| char array<br />
|-<br />
| gen<br />
| genus information<br />
| char array<br />
|-<br />
| spe<br />
| species info<br />
| char array<br />
|-<br />
| str<br />
| strain info<br />
| char array<br />
|-<br />
| typ<br />
| type<br />
| char array<br />
|-<br />
| uid<br />
| taxonomy identification number for species as used by the NCBI (see [https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi]), can be modified<br />
| char array<br />
|-<br />
| uie<br />
| unmodified taxonomy identification number for strains used by the NCBI (see [https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi])<br />
| char array<br />
|-<br />
| gti<br />
| cultivation conditions: growth time<br />
| char array<br />
|-<br />
| tem<br />
| cultivation conditions: cultivation temperature<br />
| char array<br />
|-<br />
| air<br />
| cultivation conditions: cultivation under aerobic or anaerobic conditions<br />
| char array<br />
|-<br />
| med<br />
| cultivation conditions: cultivation medium<br />
| char array<br />
|-<br />
| spo<br />
| spore formers (Yes or No)<br />
| char array<br />
|-<br />
| con<br />
| sample concentration<br />
| char array<br />
|-<br />
| trt <br />
| sample treatment<br />
| char array<br />
|-<br />
| ext <br />
| extra information<br />
| char array<br />
|-<br />
| las <br />
| laser parameters (power, spot diameter, frequency, etc.)<br />
| char array<br />
|-<br />
| cal <br />
| calibration info<br />
| char array<br />
|-<br />
| met<br />
| measurement method<br />
| char array<br />
|-<br />
| cus <br />
| customer info<br />
| char array<br />
|-<br />
| tim <br />
| date and time of measurement<br />
| char array<br />
|-<br />
| pth<br />
| path to spectrum<br />
| char array<br />
|-<br />
| cls<br />
| class assignment (valid values are 0,1,2,3 and 4)<br />
| float32<br />
|-<br />
| lst<br />
| formatted text containing the peak table info<br />
| char array<br />
|-<br />
| seq<br />
| sequence of pre-processing steps<br />
| char array<br />
|-<br />
| smo<br />
| the number of smoothing points (Savitzky-Golay smoothing)<br />
| char array<br />
|-<br />
| bas<br />
| number of intervals used for baseline correction<br />
| float32<br />
|-<br />
| nrm<br />
| normalization parameter (Yes:1, No:0)<br />
| float32<br />
|-<br />
| clb<br />
| calibration parameters (not used)<br />
| float32<br />
|-<br />
| red<br />
| data reduction factor (spectral binning)<br />
| char array<br />
|-<br />
| cut<br />
| cut in the spectral domain, m/z range<br />
| char array<br />
|-<br />
| tmp<br />
| temporary info (not always present)<br />
| char array<br />
|-<br />
| mod<br />
| original data modified by cut spectra or reduce resolution (Yes:1, No:0)<br />
| float32<br />
|-<br />
| lms<br />
| MALDI-ToF MS, or LC-MS&sup1; data? (0: MALDI, 1: LC-MS&sup1;)<br />
| float32<br />
|-<br />
| pik<br />
| [[#peak table format|peak table]], an array of the dimension [4 x npeaks] or [6 x npeaks], where npeaks denotes the number of peaks <br />
| float 32<br />
|-<br />
| ccl<br />
| [[#structure array ccl|calibration information]]<br />
| struc array<br />
|-<br />
| avr<br />
| [[#structure array avr|average spectrum]]<br />
| struc array<br />
|-<br />
| dbs<br />
| [[#structure array dbs|data base spectrum]]<br />
| struc array<br />
|-<br />
| prm<br />
| parameters of peak detection<br />
| char array<br />
|-<br />
| qt<br />
| quality test parameter<br />
| struc array<br />
|-<br />
|}<br />
<br />
== Peak table format - '''''spec.pik''''' ==<br />
<br />
<span class="mw-headline" id="peak table format"></span><br />
<br><br />
{| class="wikitable" width=800<br />
!width=100| Fields<br />
!width=700| Description<br />
|-<br />
| spec.pik(1,:) <br> &nbsp; <br><br />
| m/z positions of the peaks in the peak table <br> &nbsp; <br> <br />
|-<br />
| spec.pik(2,:) <br> &nbsp; <br><br />
| absolute intensities of these peaks <br> &nbsp; <br><br />
|-<br />
| spec.pik(3,:) <br> &nbsp; <br><br />
| weighting factors (the sum of these factors equals 100) <br> &nbsp; <br><br />
|-<br />
| spec.pik(4,:) <br> &nbsp; <br><br />
| in case of single spectra, i.e. no database or average spectra: baseline-corrected absolute intensities of the peaks, in case of average or database spectra: the relative peak frequency<br />
|-<br />
| spec.pik(5,:) <br> &nbsp; <br><br />
| FWHH of the given peak (requires QT) <br> &nbsp; <br><br />
|-<br />
| spec.pik(6,:) <br> &nbsp; <br><br />
| resolving power of the given peak (requires QT) <br> &nbsp; <br><br />
|}<br />
<br />
<br />
== Calibration information - '''''spec.ccl''''' ==<br />
<br />
<span class="mw-headline" id="structure array ccl"></span><br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| cl1<br />
| calibration constant 1<br />
| float32<br />
| rowspan="15" style="background: #ffffff;" valign="top" | [[File:calibration-format-spec-struc.png|250px|thumb|center|Screenshot showing the content of the structure array spec.ccl containing the calibration info (calibration constants, delay time, number of spectrum data points, etc.)]]<br />
|-<br />
| cl2<br />
| calibration constant 2<br />
| float32<br />
|-<br />
| cl3<br />
| calibration constant 3<br />
| float32<br />
|-<br />
| del <br />
| delay time [ns]<br />
| float32<br />
|-<br />
| npt<br />
| number of data points<br />
| float32<br />
|-<br />
| res <br />
| time resolution [ns]<br />
| float32<br />
|-<br />
| ncl<br />
| calibration info required to store the spectrum in a Bruker-specific data format <br />
| char array<br />
|-<br />
| ncr<br />
| calibration info required to store the spectrum in a Bruker-specific data format <br />
| char array<br />
|-<br />
| bid<br />
| hardware id of the spectrum ('Bruker ID')<br />
| char array<br />
|-<br />
| mid<br />
| MicrobeMS id of the spectrum<br />
| char array<br />
|-<br />
| org<br />
| manufacturer info<br />
| char array<br />
|-<br />
| tfu<br />
| 'ToF user'<br />
| char array<br />
|-<br />
| spm<br />
| not used<br />
| char array<br />
|-<br />
| stp<br />
| type of measurement (should be 'TOF')<br />
| char array<br />
|-<br />
| acq<br />
| further acquisition info<br />
| char array<br />
|}<br />
<br />
<br />
== Database spectra - '''''spec.dbs''''' ==<br />
<br />
<span class="mw-headline" id="structure array dbs"></span><br />
<br><br />
A [[Create database spectra|database spectrum]] is usually created from many (>3) individual mass spectra. Like in regular experimental spectra, spectral data and metadata of average spectra are stored in specific fields of structure array ''spec''. In database spectra the field ''spec(i).dbs'' is used to store relevant data from experimental source spectra from which the given database spectrum has been derived. These fields are left empty in experimental and average spectra. Details of the structure of ''spec.dbs'' are given in the table below. <br />
<br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| mem<br />
| specifies whether the current spectrum is a data base spectrum (1) or not (0)<br />
| char array<br />
| rowspan="5" style="background: #ffffff;" valign="top" |[[File:dbs-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''spec.dbs''. This screenshot shows information like the spectrum id, taxonomic information, peak tables, respective peak detection parameters, etc of mass spectrum #1 [spec(1).dbs(1,1)] that was used with others to obtain a database spectrum]]<br />
|-<br />
| ids<br />
| id's of the individual mass spectra that contributed to the given database spectrum<br />
| char array<br />
|-<br />
| tax<br />
| contains taxonomical information (i.e. the genus, species, strain information)<br />
| char array<br />
|-<br />
| pik<br />
| peak table of the given source spectrum <br />
| float32<br />
|-<br />
| prm<br />
| parameters used for peak detection <br />
| char array<br />
|}<br />
<br />
== Average spectra - '''''spec.avr''''' ==<br />
<br />
<span class="mw-headline" id="structure array avr"></span><br />
<br><br />
An [[Averaging Mass Spectra|average spectrum]] is usually created from many (>3) individual mass spectra. Like in regular experimental spectra, spectral data and metadata of average spectra are stored in specific fields of structure array ''spec''. In average spectra the field ''spec(i).avr'' is used to store relevant data from experimental source spectra from which the given average spectrum has been derived. These fields are empty in experimental and database spectra. Details of the structure of ''spec.avr'' are given in the table below. <br />
<br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| mem<br />
| specifies whether the contributing spectrum is an average spectrum (1) or not (0)<br />
| char array<br />
| rowspan="6" style="background: #ffffff;" valign="top" |[[File:avr-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''spec.avr''. This screenshot shows information like the spectrum id, taxonomic information, peak tables, respective peak detection parameters, etc of mass spectrum #1 [spec(1).avr(1,1)] that was used with others to obtain an average spectrum]]<br />
|-<br />
| ids<br />
| id of the individual mass spectrum that contributed to the given average spectrum<br />
| char array<br />
|-<br />
| tax<br />
| contains taxonomical information (i.e. the genus, species, strain information)<br />
| char array<br />
|-<br />
| pik<br />
| peak table of the given source spectrum <br />
| float32<br />
|-<br />
| prm<br />
| parameters used for peak detection <br />
| char array<br />
|}<br />
<br />
<br />
== Quality test results - '''''spec.qt''''' ==<br />
<br />
<span class="mw-headline" id="structure array qt"></span><br />
<br><br />
The structure array ''spec.qt'' contains the results of a [[MALDI Quality Tests|Quality Test]]. Fields of this structure are empty if no QT has been performed. Details of the structure of ''spec.qt'' are given in the table below. <br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| noise<br />
| QT data of the ''noise'' test, contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
| rowspan="7" style="background: #ffffff;" valign="top" |[[File:qt-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''spec.qt'' that contains the results of a quality test (QT).]]<br />
|-<br />
| basln<br />
| QT data of the ''baseline'' test, contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| npiks<br />
| QT data of the test ''number of peaks'', contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| respw<br />
| QT data of the test ''resolution power'', contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| rnk<br />
| overall rank that the given spectrum has achieved in a QT with a number of other spectra<br />
| float32<br />
|-<br />
| res<br />
| overall quality test score<br />
| float32<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Format_of_Spectral_Multifiles&diff=1139Format of Spectral Multifiles2026-03-09T09:55:46Z<p>Laschp: </p>
<hr />
<div>Spectra multifiles combine metadata and spectral data from multiple mass spectra in one single file. Such multifiles files are stored in a Matlab&trade; specific format, structure arrays, that contain different files for spectral data as well as metadata. Spectra multifiles can be loaded in the Matlab environment by entering the following command at the Matlab command prompt:<br />
<br />
>> load('muffname','-mat');<br />
<br />
where ''muffname'' denotes the name of the spectrum multifile. For example, the command ''load('RKI-ring-trial-spectra.muf','-mat')'' will open the file ''RKI-ring-trial-spectra.muf'', a MALDI-ToF mass spectrum multifile containing 24 individual MALDI-ToF mass spectra acquired within the ''so called'' [https://pubmed.ncbi.nlm.nih.gov/26063856/ '''RKI ring trial study''']. The file ''RKI-ring-trial-spectra.muf'' can be downloaded [https://wiki.microbe-ms.com/upload/RKI-ring-trial-spectra.muf: '''here''']. If loading was successful, you will have access to a new Matlab variable ''spec'' (struc array). Details of the structure of ''spec'' are described next.<br> &nbsp; <br><br />
<br />
== Fields of the structure array - '''''spec''''' ==<br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Data type<br />
!width=300|<br />
|-<br />
| org<br />
| original mass spectra [2 x n array], n: number of data points<br />
| float32<br />
| rowspan="41" style="background: #ffffff;" valign="top" | [[File:Multifile-format-spec-struc.png|250px|thumb|center|Screenshot showing the content of the structure array ''spec'' that is stored in ''so called'' spectrum multi files (*.muf). Fields of ''spec'' contain spectral data (original, i.e. unmodified, and pre-processed), spectrum metadata as well as peak lists, calibration information, results of quality tests, and information collected during creation of average, or database spectra. In the example of the given screenshot, the content of one database spectrum is depicted.]]<br />
|-<br />
| pre<br />
| pre-processed spectra [2 x n array], n: number of data points<br />
| float32<br />
|-<br />
| nam<br />
| spectra id<br />
| char array<br />
|-<br />
| gen<br />
| genus information<br />
| char array<br />
|-<br />
| spe<br />
| species info<br />
| char array<br />
|-<br />
| str<br />
| strain info<br />
| char array<br />
|-<br />
| typ<br />
| type<br />
| char array<br />
|-<br />
| uid<br />
| taxonomy identification number for species as used by the NCBI (see [https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi]), can be modified<br />
| char array<br />
|-<br />
| uie<br />
| unmodified taxonomy identification number for strains used by the NCBI (see [https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi])<br />
| char array<br />
|-<br />
| gti<br />
| cultivation conditions: growth time<br />
| char array<br />
|-<br />
| tem<br />
| cultivation conditions: cultivation temperature<br />
| char array<br />
|-<br />
| air<br />
| cultivation conditions: cultivation under aerobic or anaerobic conditions<br />
| char array<br />
|-<br />
| med<br />
| cultivation conditions: cultivation medium<br />
| char array<br />
|-<br />
| spo<br />
| spore formers (Yes or No)<br />
| char array<br />
|-<br />
| con<br />
| sample concentration<br />
| char array<br />
|-<br />
| trt <br />
| sample treatment<br />
| char array<br />
|-<br />
| ext <br />
| extra information<br />
| char array<br />
|-<br />
| las <br />
| laser parameters (power, spot diameter, frequency, etc.)<br />
| char array<br />
|-<br />
| cal <br />
| calibration info<br />
| char array<br />
|-<br />
| met<br />
| measurement method<br />
| char array<br />
|-<br />
| cus <br />
| customer info<br />
| char array<br />
|-<br />
| tim <br />
| date and time of measurement<br />
| char array<br />
|-<br />
| pth<br />
| path to spectrum<br />
| char array<br />
|-<br />
| cls<br />
| class assignment (valid values are 0,1,2,3 and 4)<br />
| float32<br />
|-<br />
| lst<br />
| formatted text containing the peak table info<br />
| char array<br />
|-<br />
| seq<br />
| sequence of pre-processing steps<br />
| char array<br />
|-<br />
| smo<br />
| the number of smoothing points (Savitzky-Golay smoothing)<br />
| char array<br />
|-<br />
| bas<br />
| number of intervals used for baseline correction<br />
| float32<br />
|-<br />
| nrm<br />
| normalization parameter (Yes:1, No:0)<br />
| float32<br />
|-<br />
| clb<br />
| calibration parameters (not used)<br />
| float32<br />
|-<br />
| red<br />
| data reduction factor (spectral binning)<br />
| char array<br />
|-<br />
| cut<br />
| cut in the spectral domain, m/z range<br />
| char array<br />
|-<br />
| tmp<br />
| temporary info (not always present)<br />
| char array<br />
|-<br />
| mod<br />
| original data modified by cut spectra or reduce resolution (Yes:1, No:0)<br />
| float32<br />
|-<br />
| lms<br />
| MALDI-ToF MS, or LC-MS&sup1; data? (0: MALDI, 1: LC-MS&sup1;)<br />
| float32<br />
|-<br />
| pik<br />
| [[#peak table format|peak table]], an array of the dimension [4 x npeaks] or [6 x npeaks], where npeaks denotes the number of peaks <br />
| float 32<br />
|-<br />
| ccl<br />
| [[#structure array ccl|calibration information]]<br />
| struc array<br />
|-<br />
| avr<br />
| [[#structure array avr|average spectrum]]<br />
| struc array<br />
|-<br />
| dbs<br />
| [[#structure array dbs|data base spectrum]]<br />
| struc array<br />
|-<br />
| prm<br />
| parameters of peak detection<br />
| char array<br />
|-<br />
| qt<br />
| quality test parameter<br />
| struc array<br />
|-<br />
|}<br />
<br />
== Peak table format - '''''spec.pik''''' ==<br />
<br />
<span class="mw-headline" id="peak table format"></span><br />
<br><br />
{| class="wikitable" width=800<br />
!width=100| Fields<br />
!width=700| Description<br />
|-<br />
| spec.pik(1,:) <br> &nbsp; <br><br />
| m/z positions of the peaks in the peak table <br> &nbsp; <br> <br />
|-<br />
| spec.pik(2,:) <br> &nbsp; <br><br />
| absolute intensities of these peaks <br> &nbsp; <br><br />
|-<br />
| spec.pik(3,:) <br> &nbsp; <br><br />
| weighting factors (the sum of these factors equals 100) <br> &nbsp; <br><br />
|-<br />
| spec.pik(4,:) <br> &nbsp; <br><br />
| in case of single spectra, i.e. no database or average spectra: baseline-corrected absolute intensities of the peaks, in case of average or database spectra: the relative peak frequency<br />
|-<br />
| spec.pik(5,:) <br> &nbsp; <br><br />
| FWHH of the given peak (requires QT) <br> &nbsp; <br><br />
|-<br />
| spec.pik(6,:) <br> &nbsp; <br><br />
| resolving power of the given peak (requires QT) <br> &nbsp; <br><br />
|}<br />
<br />
<br />
== Calibration information - '''''spec.ccl''''' ==<br />
<br />
<span class="mw-headline" id="structure array ccl"></span><br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| cl1<br />
| calibration constant 1<br />
| float32<br />
| rowspan="15" style="background: #ffffff;" valign="top" | [[File:calibration-format-spec-struc.png|250px|thumb|center|Screenshot showing the content of the structure array spec.ccl containing the calibration info (calibration constants, delay time, number of spectrum data points, etc.)]]<br />
|-<br />
| cl2<br />
| calibration constant 2<br />
| float32<br />
|-<br />
| cl3<br />
| calibration constant 3<br />
| float32<br />
|-<br />
| del <br />
| delay time [ns]<br />
| float32<br />
|-<br />
| npt<br />
| number of data points<br />
| float32<br />
|-<br />
| res <br />
| time resolution [ns]<br />
| float32<br />
|-<br />
| ncl<br />
| calibration info required to store the spectrum in a Bruker-specific data format <br />
| char array<br />
|-<br />
| ncr<br />
| calibration info required to store the spectrum in a Bruker-specific data format <br />
| char array<br />
|-<br />
| bid<br />
| hardware id of the spectrum ('Bruker ID')<br />
| char array<br />
|-<br />
| mid<br />
| MicrobeMS id of the spectrum<br />
| char array<br />
|-<br />
| org<br />
| manufacturer info<br />
| char array<br />
|-<br />
| tfu<br />
| 'ToF user'<br />
| char array<br />
|-<br />
| spm<br />
| not used<br />
| char array<br />
|-<br />
| stp<br />
| type of measurement (should be 'TOF')<br />
| char array<br />
|-<br />
| acq<br />
| further acquisition info<br />
| char array<br />
|}<br />
<br />
<br />
== Database spectra - '''''spec.dbs''''' ==<br />
<br />
<span class="mw-headline" id="structure array dbs"></span><br />
<br><br />
A [[Create database spectra|database spectrum]] is usually created from many (>3) individual mass spectra. Like in regular experimental spectra, spectral data and metadata of average spectra are stored in specific fields of structure array ''spec''. In database spectra the field ''spec(i).dbs'' is used to store relevant data from experimental source spectra from which the given database spectrum has been derived. These fields are left empty in experimental and average spectra. Details of the structure of ''spec.dbs'' are given in the table below. <br />
<br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| mem<br />
| specifies whether the current spectrum is a data base spectrum (1) or not (0)<br />
| char array<br />
| rowspan="5" style="background: #ffffff;" valign="top" |[[File:dbs-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''spec.dbs''. This screenshot shows information like the spectrum id, taxonomic information, peak tables, respective peak detection parameters, etc of mass spectrum #1 [spec(1).dbs(1,1)] that was used with others to obtain a database spectrum]]<br />
|-<br />
| ids<br />
| id of the individual mass spectrum that contributed to the given database spectrum<br />
| char array<br />
|-<br />
| tax<br />
| contains taxonomical information (i.e. the genus, species, strain information)<br />
| char array<br />
|-<br />
| pik<br />
| peak table of the given source spectrum <br />
| float32<br />
|-<br />
| prm<br />
| parameters used for peak detection <br />
| char array<br />
|}<br />
<br />
== Average spectra - '''''spec.avr''''' ==<br />
<br />
<span class="mw-headline" id="structure array avr"></span><br />
<br><br />
An [[Averaging Mass Spectra|average spectrum]] is usually created from many (>3) individual mass spectra. Like in regular experimental spectra, spectral data and metadata of average spectra are stored in specific fields of structure array ''spec''. In average spectra the field ''spec(i).avr'' is used to store relevant data from experimental source spectra from which the given average spectrum has been derived. These fields are empty in experimental and database spectra. Details of the structure of ''spec.avr'' are given in the table below. <br />
<br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| mem<br />
| specifies whether the contributing spectrum is an average spectrum (1) or not (0)<br />
| char array<br />
| rowspan="6" style="background: #ffffff;" valign="top" |[[File:avr-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''spec.avr''. This screenshot shows information like the spectrum id, taxonomic information, peak tables, respective peak detection parameters, etc of mass spectrum #1 [spec(1).avr(1,1)] that was used with others to obtain an average spectrum]]<br />
|-<br />
| ids<br />
| id of the individual mass spectrum that contributed to the given average spectrum<br />
| char array<br />
|-<br />
| tax<br />
| contains taxonomical information (i.e. the genus, species, strain information)<br />
| char array<br />
|-<br />
| pik<br />
| peak table of the given source spectrum <br />
| float32<br />
|-<br />
| prm<br />
| parameters used for peak detection <br />
| char array<br />
|}<br />
<br />
<br />
== Quality test results - '''''spec.qt''''' ==<br />
<br />
<span class="mw-headline" id="structure array qt"></span><br />
<br><br />
The structure array ''spec.qt'' contains the results of a [[MALDI Quality Tests|Quality Test]]. Fields of this structure are empty if no QT has been performed. Details of the structure of ''spec.qt'' are given in the table below. <br />
<br><br />
{| class="wikitable" width=1100<br />
!width=100| Fields<br />
!width=600| Description<br />
!width=100| Type<br />
!width=300| <br />
|-<br />
| noise<br />
| QT data of the ''noise'' test, contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
| rowspan="7" style="background: #ffffff;" valign="top" |[[File:qt-format-spec-struc.png|250px|thumb|center|Screenshot of structure array ''spec.qt'' that contains the results of a quality test (QT).]]<br />
|-<br />
| basln<br />
| QT data of the ''baseline'' test, contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| npiks<br />
| QT data of the test ''number of peaks'', contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| respw<br />
| QT data of the test ''resolution power'', contains fields ''abs'', ''rnk'', and ''obj''<br />
| struc array<br />
|-<br />
| rnk<br />
| overall rank that the given spectrum has achieved in a QT with a number of other spectra<br />
| float32<br />
|-<br />
| res<br />
| overall quality test score<br />
| float32<br />
|}</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=MicrobeMS_-_A_Matlab_Toolbox_for_Microbial_Identification_Based_on_Mass_Spectrometry&diff=1138MicrobeMS - A Matlab Toolbox for Microbial Identification Based on Mass Spectrometry2026-03-09T09:39:01Z<p>Laschp: /* Getting Started */</p>
<hr />
<div>== Introduction ==<br />
<br />
The MicrobeMS software package is a program specifically designed for the analysis of MALDI-ToF mass spectra of microbial samples. The software was developed by [http://www.peter-lasch.de: Peter Lasch] at the [https://www.rki.de Robert-Koch-Institute (RKI)] in Berlin/Germany and can be used to identify microbial species based on their mass spectral patterns. The program is a comprehensive [http://www.mathworks.com: Matlab]-based package that operates under Windows 7/8/8.1/10/11 and LINUX (Debian, MicrobeMS versions later than 0.81). Original MALDI-ToF mass spectra in the format defined by [http://www.bdal.com: Bruker Daltonics] or by [http://www.shimadzu.com: Shimadzu] (via the mzXML data format) can be imported, processed and converted into a Matlab data matrix format specific to the MicrobeMS program.<br />
<br />
The software allows standard mass spectrometry manipulations such as smoothing, baseline correction, normalization, peak detection, auto-calibration to mention some preprocessing functions. Furthermore, functionalities of the software include, among others, microbial identification analysis based on spectral distances and machine learning methods (ML), e.g. by artificial neural networks (ANN) with visualization of the identification results, unsupervised hierarchical cluster analysis, biomarker analysis, pseudo-gel view generation, as well as microbial mass spectra database management including interfaces for organizing mass spectral metadata. Since the software also runs in a full Windows, or LINUX, 64-bit environment, the number of spectra in the data sets is limited only by the amount of available memory (RAM).<br><br />
<br />
== Getting Started ==<br />
* [[download_MicrobeMS|Downloading MicrobeMS]]<br />
* [[computer_specification|Specification of computer configuration]]<br />
* [[install_MicrobeMS|How to install MicrobeMS]]<br />
* [[Screenshot_of_MicrobeMS|Screenshot]] of the main gui<br />
* [[MicrobeMS_Wiki:General_disclaimer |License conditions]]<br />
* [[How_to_Obtain_a_License|How to obtain a license key]]<br />
* [[Mass Spectrometry Databases|Mass spectrometry databases]]<br />
* [[Publications_with_MicrobeMS|Publications with MicrobeMS, acknowledgements]]<br />
* [[Other MALDI-ToF MS Ressources|Other MALDI-ToF MS ressources]]<br />
* [[Frequently_Asked_Questions_(FAQ)|Frequently asked questions (FAQ)]]<br />
<br />
== Management of Metadata Information ==<br />
<br />
* [[Adding / Editing Metadata of MALDI-TOF Mass Spectral Data|Adding / editing metadata of MS data files]] (spectrum metadata, taxonomic information, culture conditions, sample preparation methods, etc.)<br />
<br />
== Description of Data File Formats Specific to MicrobeMS ==<br />
* [[Data_Format_of_Spectral_Multifiles|Description of the format of spectral multifiles (*.muf)]]<br />
* [[Data_Format_of_Peak_List_Files|Description of the format of peak list files (*.pkf)]]<br />
* Description of the format of quality test files (*.mat)<br />
<!-- commented out * [[Format_of_Quality_Test_Result_Files|Description of the format of quality test files (*.mat)]] --><br />
* [[Description of MicrobeMS' main parameter file 'microbems.opt'|Description of the parameter file ''microbems.opt'']]<br />
<br />
== Import and Export of Mass Spectra and Mass Spectral Libraries ==<br />
<br />
* [[Load spectra (Bruker format)|Load spectral data files]] acquired by Bruker Daltonics MALDI-ToF mass spectrometers<br />
* [[Data_Format_of_Spectral_Multifiles|Load / store spectral multifiles (*.muf)]]<br />
* [[Data_Format_of_Peak_List_Files|Load / store peak list files (*.pkf)]]<br />
* [[Store spectra (Bruker format)|Store spectra in a Bruker-specific data format]]<br />
* [[Export spectra to ASCII|Store spectra in a standard ASCII data format]] (export to ASCII)<br />
* [[Store spectra (NeuroDeveloper format)|Store peaklist data in a format specific to the NeuroDeveloper software]] (export to NeuroDeveloper)<br />
* [[Import Mass Spectra in a mzXML Data Format|Import mass spectral data from mzXML data]] (allows importing spectra from Shimadzu/bioMérieux systems)<br />
* [[Export XML Data|Export XML Data]] (required for identification analysis with MicrobeNet from the CDC)<br />
<br />
== Spectral Analysis and Visualization ==<br />
* [[Spectral Pre-processing|Spectral pre-processing]]: smoothing, baseline correction, normalization, cut, auto-calibration, reduce resolution (binning)<br />
* [[MALDI Quality Tests|Quality tests of MALDI-ToF mass spectra]]<br />
* [[Peak Detection|Peak detection]]<br />
* [[Averaging Mass Spectra|Averaging mass spectra]]<br />
* [[Display MS Metadata|Display spectral metadata]]<br />
* [[The Log-File (logfile.txt)|The log-file]] (logfile.txt)<br />
<br />
== Identification and Classification ==<br />
<br />
* [[Unsupervised Hierarchical Cluster Analysis|Unsupervised hierarchical cluster analysis]] <br />
* [[Create database spectra|Creating database spectra from individual microbial mass spectra]]<br />
* Compiling mass spectral databases<br />
* [[Microbial Identification based on Mass Spectral Libraries and Interspectral Distances|Microbial identification based on mass spectral libraries and interspectral distances]]<br />
* [[Identification Analysis by Neural Networks|Identification analysis by artificial neural networks (ANN,]] requires the NeuroDeveloper software package from [http://www.synthon-analytics.de: Synthon Analytics])<br />
* [[Identification Analysis by Means of LC-MS&sup1; and ''in silico'' Databases|Identification analysis by means of LC-MS&sup1; and ''in silico'' databases]]<br />
<br />
== Identification of MS Biomarker Peaks ==<br />
<br />
* Generation of [[Creating Pseudo-Gel Views|''pseudo-gel'' views]] from microbial mass spectra<br />
* [[Class Assignment|How to perform class assignments]]<br />
* [[Peak Frequency Test|Peak frequency tests]]<br />
* [[Two-samples t-Tests|Two-samples t-tests]]<br />
* [[Wilcoxon Rank-Sum Test|Wilcoxon rank-sum tests]]</div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Other_MALDI-ToF_MS_Ressources&diff=1137Other MALDI-ToF MS Ressources2026-03-08T12:29:04Z<p>Laschp: </p>
<hr />
<div>Below is a list of resources that may be useful for MALDI-ToF MS-based identification of bacteria. This list is not exhaustive and will be updated regularly. Please report outdated links (''lasch at microbe-ms dot com'').<br><br />
<br />
[[File:MALDI-workflow.png|500px|right|thumb|Workflow of microbial identification using MALDI-ToF MS (Copyright Peter Lasch, RKI Berlin, 2025)]]<br />
<br />
<ul><br />
<li> [https://www.bruker.com/en/applications/microbiology-and-diagnostics/microbiological-research/maldi-biotyper-for-microbial-research.html MALDI Biotyper] (MBT), a commercial solution for microbial research from Bruker Daltonics</li><br />
<br />
<li> [https://www.biomerieux.com/us/en/our-offer/clinical-products/vitek-ms-prime.html VITEK MS PRIME] MALDI-ToF mass spectrometry from bioMérieux for routine microbial identification (commercial)</li><br />
<br />
<li> [https://microbenet.cdc.gov/ MicrobeNet], a free online resource maintained by the Centers for Disease Control and Prevention (CDC, Atlanta, USA)</li><br />
<br />
<li> [https://spectrometrylab.wordpress.com/ Open Source Spectrometry] - Matthias Mailänder's Blog (OpenChrom, Lablicate)</li><br />
<br />
<li> [https://maldi-up.ua-bw.de/index.asp MALDI-UP] - a free catalogue enabling the exchange of MALDI-TOF-MS spectra between users working in the field of microbiology, food analytics and in other fields, hosted at the CVUA Stuttgart</li><br />
<br />
<li> [https://www.longdom.org/open-access/biospean-a-freeware-tool-for-processing-spectra-from-maldi-intact-cellspore-mass-spectrometry-33447.html Biospean] - a freeware tool for processing spectra from MALDI intact cell/spore mass spectrometry</li><br />
<br />
<li> [https://idbac.org/ IDBac] - a place to ID bacteria, organize strain collections & ask research questions </li><br />
<br />
<li> [https://mabritec.com/en/ Mabritec & Mabriteccentral] - comprehensive ''in silico'' MALDI-ToF MS databases as attractive alternatives for fast, accurate and cost-effective germ identification<br />
<br />
<li> [https://maldibot.ar/ MALDI-BOT] - an AI assistant specialized in interpretation of mass spectrometry results (RENAEM, Argentina)<br />
<br />
</ul><br />
<br />
<!-- externe MALDI Datenbanken und MPS Sammlungen--> <br />
<br />
<!-- chinesische Hersteller von MS Lösungen --> <br />
<br />
<!-- Andromas? --><br />
<br />
<!-- nachschauen: https://maldi-up.ua-bw.de/tools.asp --></div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Other_MALDI-ToF_MS_Ressources&diff=1136Other MALDI-ToF MS Ressources2026-03-08T10:51:55Z<p>Laschp: </p>
<hr />
<div>Below is a list of resources that may be useful for MALDI-ToF MS-based identification of bacteria. This list is not exhaustive and will be updated regularly. Please report outdated links (''lasch at microbe-ms dot com'').<br><br />
<br />
[[File:MALDI-workflow.png|500px|right|thumb|Workflow of microbial identification using MALDI-ToF MS (Copyright Peter Lasch, RKI Berlin, 2025)]]<br />
<br />
<ul><br />
<li> [https://www.bruker.com/en/applications/microbiology-and-diagnostics/microbiological-research/maldi-biotyper-for-microbial-research.html MALDI Biotyper] (MBT), a commercial solution for microbial research from Bruker Daltonics</li><br />
<br />
<li> [https://www.biomerieux.com/us/en/our-offer/clinical-products/vitek-ms-prime.html VITEK MS PRIME] MALDI-ToF mass spectrometry from bioMérieux for routine microbial identification (commercial)</li><br />
<br />
<li> [https://microbenet.cdc.gov/ MicrobeNet], a free online resource maintained by the Centers for Disease Control and Prevention (CDC, Atlanta, USA)</li><br />
<br />
<li> [https://spectrometrylab.wordpress.com/ Open Source Spectrometry] - Matthias Mailänder's Blog (OpenChrom, Lablicate)</li><br />
<br />
<li> [https://maldi-up.ua-bw.de/index.asp MALDI-UP] - a free catalogue enabling the exchange of MALDI-TOF-MS spectra between users working in the field of microbiology, food analytics and in other fields, hosted at the CVUA Stuttgart</li><br />
<br />
<li> [https://www.longdom.org/open-access/biospean-a-freeware-tool-for-processing-spectra-from-maldi-intact-cellspore-mass-spectrometry-33447.html Biospean] - a freeware tool for processing spectra from MALDI intact cell/spore mass spectrometry</li><br />
<br />
<li> [https://idbac.org/ IDBac] - a place to ID bacteria, organize strain collections & ask research questions </li><br />
<br />
<li> [https://mabritec.com/en// Mabritec & Mabriteccentral] - comprehensive ''in silico'' MALDI-ToF MS databases as attractive alternatives for fast, accurate and cost-effective germ identification<br />
<br />
</ul><br />
<br />
<!-- externe MALDI Datenbanken und MPS Sammlungen--> <br />
<br />
<!-- chinesische Hersteller von MS Lösungen --> <br />
<br />
<!-- Andromas? --></div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Other_MALDI-ToF_MS_Ressources&diff=1135Other MALDI-ToF MS Ressources2026-03-08T10:51:26Z<p>Laschp: </p>
<hr />
<div>Below is a list of resources that may be useful for MALDI-ToF MS-based identification of bacteria. This list is not exhaustive and will be updated regularly. Please report outdated links (''lasch at microbe-ms dot com'').<br><br />
<br />
[[File:MALDI-workflow.png|500px|right|thumb|Workflow of microbial identification using MALDI-ToF MS (Copyright Peter Lasch, RKI Berlin, 2025)]]<br />
<br />
<ul><br />
<li> [https://www.bruker.com/en/applications/microbiology-and-diagnostics/microbiological-research/maldi-biotyper-for-microbial-research.html MALDI Biotyper] (MBT), a commercial solution for microbial research from Bruker Daltonics</li><br />
<br />
<li> [https://www.biomerieux.com/us/en/our-offer/clinical-products/vitek-ms-prime.html VITEK MS PRIME] MALDI-ToF mass spectrometry from bioMérieux for routine microbial identification (commercial)</li><br />
<br />
<li> [https://microbenet.cdc.gov/ MicrobeNet], a free online resource maintained by the Centers for Disease Control and Prevention (CDC, Atlanta, USA)</li><br />
<br />
<li> [https://spectrometrylab.wordpress.com/ Open Source Spectrometry] - Matthias Mailänder's Blog (OpenChrom, Lablicate)</li><br />
<br />
<li> [https://maldi-up.ua-bw.de/index.asp MALDI-UP] - a free catalogue enabling the exchange of MALDI-TOF-MS spectra between users working in the field of microbiology, food analytics and in other fields, hosted at the CVUA Stuttgart</li><br />
<br />
<li> [https://www.longdom.org/open-access/biospean-a-freeware-tool-for-processing-spectra-from-maldi-intact-cellspore-mass-spectrometry-33447.html Biospean] - a freeware tool for processing spectra from MALDI intact cell/spore mass spectrometry</li><br />
<br />
<li> [https://idbac.org/ IDBac] - a place to ID bacteria, organize strain collections & ask research questions </li><br />
<br />
<li> [https://mabritec.com/en// Mabritec & Mabriteccentral] - a comprehensive ''in silico'' MALDI-ToF MS databases as attractive alternatives for fast, accurate and cost-effective germ identification<br />
<br />
</ul><br />
<br />
<!-- externe MALDI Datenbanken und MPS Sammlungen--> <br />
<br />
<!-- chinesische Hersteller von MS Lösungen --> <br />
<br />
<!-- Andromas? --></div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Other_MALDI-ToF_MS_Ressources&diff=1134Other MALDI-ToF MS Ressources2026-03-08T10:51:04Z<p>Laschp: </p>
<hr />
<div>Below is a list of resources that may be useful for MALDI-ToF MS-based identification of bacteria. This list is not exhaustive and will be updated regularly. Please report outdated links (lasch at microbe-ms dot com).<br><br />
<br />
[[File:MALDI-workflow.png|500px|right|thumb|Workflow of microbial identification using MALDI-ToF MS (Copyright Peter Lasch, RKI Berlin, 2025)]]<br />
<br />
<ul><br />
<li> [https://www.bruker.com/en/applications/microbiology-and-diagnostics/microbiological-research/maldi-biotyper-for-microbial-research.html MALDI Biotyper] (MBT), a commercial solution for microbial research from Bruker Daltonics</li><br />
<br />
<li> [https://www.biomerieux.com/us/en/our-offer/clinical-products/vitek-ms-prime.html VITEK MS PRIME] MALDI-ToF mass spectrometry from bioMérieux for routine microbial identification (commercial)</li><br />
<br />
<li> [https://microbenet.cdc.gov/ MicrobeNet], a free online resource maintained by the Centers for Disease Control and Prevention (CDC, Atlanta, USA)</li><br />
<br />
<li> [https://spectrometrylab.wordpress.com/ Open Source Spectrometry] - Matthias Mailänder's Blog (OpenChrom, Lablicate)</li><br />
<br />
<li> [https://maldi-up.ua-bw.de/index.asp MALDI-UP] - a free catalogue enabling the exchange of MALDI-TOF-MS spectra between users working in the field of microbiology, food analytics and in other fields, hosted at the CVUA Stuttgart</li><br />
<br />
<li> [https://www.longdom.org/open-access/biospean-a-freeware-tool-for-processing-spectra-from-maldi-intact-cellspore-mass-spectrometry-33447.html Biospean] - a freeware tool for processing spectra from MALDI intact cell/spore mass spectrometry</li><br />
<br />
<li> [https://idbac.org/ IDBac] - a place to ID bacteria, organize strain collections & ask research questions </li><br />
<br />
<li> [https://mabritec.com/en// Mabritec & Mabriteccentral] - a comprehensive ''in silico'' MALDI-ToF MS databases as attractive alternatives for fast, accurate and cost-effective germ identification<br />
<br />
</ul><br />
<br />
<!-- externe MALDI Datenbanken und MPS Sammlungen--> <br />
<br />
<!-- chinesische Hersteller von MS Lösungen --> <br />
<br />
<!-- Andromas? --></div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Other_MALDI-ToF_MS_Ressources&diff=1133Other MALDI-ToF MS Ressources2026-03-08T10:50:26Z<p>Laschp: </p>
<hr />
<div>Below is a list of resources that may be useful for MALDI-ToF MS-based identification of bacteria. This list is not exhaustive and will be updated regularly. Please report outdated links (lasch at microbems dot com).<br><br />
<br />
[[File:MALDI-workflow.png|500px|right|thumb|Workflow of microbial identification using MALDI-ToF MS (Copyright Peter Lasch, RKI Berlin, 2025)]]<br />
<br />
<ul><br />
<li> [https://www.bruker.com/en/applications/microbiology-and-diagnostics/microbiological-research/maldi-biotyper-for-microbial-research.html MALDI Biotyper] (MBT), a commercial solution for microbial research from Bruker Daltonics</li><br />
<br />
<li> [https://www.biomerieux.com/us/en/our-offer/clinical-products/vitek-ms-prime.html VITEK MS PRIME] MALDI-ToF mass spectrometry from bioMérieux for routine microbial identification (commercial)</li><br />
<br />
<li> [https://microbenet.cdc.gov/ MicrobeNet], a free online resource maintained by the Centers for Disease Control and Prevention (CDC, Atlanta, USA)</li><br />
<br />
<li> [https://spectrometrylab.wordpress.com/ Open Source Spectrometry] - Matthias Mailänder's Blog (OpenChrom, Lablicate)</li><br />
<br />
<li> [https://maldi-up.ua-bw.de/index.asp MALDI-UP] - a free catalogue enabling the exchange of MALDI-TOF-MS spectra between users working in the field of microbiology, food analytics and in other fields, hosted at the CVUA Stuttgart</li><br />
<br />
<li> [https://www.longdom.org/open-access/biospean-a-freeware-tool-for-processing-spectra-from-maldi-intact-cellspore-mass-spectrometry-33447.html Biospean] - a freeware tool for processing spectra from MALDI intact cell/spore mass spectrometry</li><br />
<br />
<li> [https://idbac.org/ IDBac] - a place to ID bacteria, organize strain collections & ask research questions </li><br />
<br />
<li> [https://mabritec.com/en// Mabritec & Mabriteccentral] - a comprehensive ''in silico'' MALDI-ToF MS databases as attractive alternatives for fast, accurate and cost-effective germ identification<br />
<br />
</ul><br />
<br />
<!-- externe MALDI Datenbanken und MPS Sammlungen--> <br />
<br />
<!-- chinesische Hersteller von MS Lösungen --> <br />
<br />
<!-- Andromas? --></div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Other_MALDI-ToF_MS_Ressources&diff=1132Other MALDI-ToF MS Ressources2026-03-08T10:48:49Z<p>Laschp: </p>
<hr />
<div>Below is a list of resources that may be useful for MALDI-ToF MS-based identification of bacteria. This list is not exhaustive and will be updated regularly. Please report outdated links.<br><br />
<br />
[[File:MALDI-workflow.png|500px|right|thumb|Workflow of microbial identification using MALDI-ToF MS (Copyright Peter Lasch, RKI Berlin, 2025)]]<br />
<br />
<ul><br />
<li> [https://www.bruker.com/en/applications/microbiology-and-diagnostics/microbiological-research/maldi-biotyper-for-microbial-research.html MALDI Biotyper] (MBT), a commercial solution for microbial research from Bruker Daltonics</li><br />
<br />
<li> [https://www.biomerieux.com/us/en/our-offer/clinical-products/vitek-ms-prime.html VITEK MS PRIME] MALDI-ToF mass spectrometry from bioMérieux for routine microbial identification (commercial)</li><br />
<br />
<li> [https://microbenet.cdc.gov/ MicrobeNet], a free online resource maintained by the Centers for Disease Control and Prevention (CDC, Atlanta, USA)</li><br />
<br />
<li> [https://spectrometrylab.wordpress.com/ Open Source Spectrometry] - Matthias Mailänder's Blog (OpenChrom, Lablicate)</li><br />
<br />
<li> [https://maldi-up.ua-bw.de/index.asp MALDI-UP] - a free catalogue enabling the exchange of MALDI-TOF-MS spectra between users working in the field of microbiology, food analytics and in other fields, hosted at the CVUA Stuttgart</li><br />
<br />
<li> [https://www.longdom.org/open-access/biospean-a-freeware-tool-for-processing-spectra-from-maldi-intact-cellspore-mass-spectrometry-33447.html Biospean] - a freeware tool for processing spectra from MALDI intact cell/spore mass spectrometry</li><br />
<br />
<li> [https://idbac.org/ IDBac] - a place to ID bacteria, organize strain collections & ask research questions </li><br />
<br />
<li> [https://mabritec.com/en// Mabritec & Mabriteccentral] - a comprehensive ''in silico'' MALDI-ToF MS databases as attractive alternatives for fast, accurate and cost-effective germ identification<br />
<br />
</ul><br />
<br />
<!-- externe MALDI Datenbanken und MPS Sammlungen--> <br />
<br />
<!-- chinesische Hersteller von MS Lösungen --> <br />
<br />
<!-- Andromas? --></div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Other_MALDI-ToF_MS_Ressources&diff=1131Other MALDI-ToF MS Ressources2026-03-08T10:48:20Z<p>Laschp: </p>
<hr />
<div>Below is a list of resources that may be useful for MALDI-ToF MS-based identification of bacteria. This list is not exhaustive and will be updated regularly. Please report outdated links.<br><br />
<br />
[[File:MALDI-workflow.png|500px|right|thumb|Workflow of microbial identification using MALDI-ToF MS (Copyright Peter Lasch, RKI Berlin, 2025)]]<br />
<br />
<ul><br />
<li> [https://www.bruker.com/en/applications/microbiology-and-diagnostics/microbiological-research/maldi-biotyper-for-microbial-research.html MALDI Biotyper] (MBT), a commercial solution for microbial research from Bruker Daltonics</li><br />
<br />
<li> [https://www.biomerieux.com/us/en/our-offer/clinical-products/vitek-ms-prime.html VITEK MS PRIME] MALDI-ToF mass spectrometry from bioMérieux for routine microbial identification (commercial)</li><br />
<br />
<li> [https://microbenet.cdc.gov/ MicrobeNet], a free online resource maintained by the Centers for Disease Control and Prevention (CDC, Atlanta, USA)</li><br />
<br />
<li> [https://spectrometrylab.wordpress.com/ Open Source Spectrometry] - Matthias Mailänder's Blog (OpenChrom, Lablicate)</li><br />
<br />
<li> [https://maldi-up.ua-bw.de/index.asp MALDI-UP] - a free catalogue enabling the exchange of MALDI-TOF-MS spectra between users working in the field of microbiology, food analytics and in other fields, hosted at the CVUA Stuttgart</li><br />
<br />
<li> [https://www.longdom.org/open-access/biospean-a-freeware-tool-for-processing-spectra-from-maldi-intact-cellspore-mass-spectrometry-33447.html Biospean] - a freeware tool for processing spectra from MALDI intact cell/spore mass spectrometry</li><br />
<br />
<li> [https://idbac.org/ IDBac] - a place to ID bacteria, organize strain collections & ask research questions </li><br />
<br />
<li> [https://mabritec.com/en// Mabritec & Mabriteccentral] - a comprehensive ''in silico'' MALDI-ToF MS databases as attractive alternatives for fast, accurate and cost-effective germ identification.<br />
<br />
</ul><br />
<br />
<!-- externe MALDI Datenbanken und MPS Sammlungen--> <br />
<br />
<!-- chinesische Hersteller von MS Lösungen --> <br />
<br />
<!-- Andromas? --></div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Other_MALDI-ToF_MS_Ressources&diff=1130Other MALDI-ToF MS Ressources2026-03-08T10:47:35Z<p>Laschp: </p>
<hr />
<div>Below is a list of resources that may be useful for MALDI-ToF MS-based identification of bacteria. This list is not exhaustive and will be updated regularly. Please report outdated links.<br><br />
<br />
[[File:MALDI-workflow.png|500px|right|thumb|Workflow of microbial identification using MALDI-ToF MS (Copyright Peter Lasch, RKI Berlin, 2025)]]<br />
<br />
<ul><br />
<li> [https://www.bruker.com/en/applications/microbiology-and-diagnostics/microbiological-research/maldi-biotyper-for-microbial-research.html MALDI Biotyper] (MBT), a commercial solution for microbial research from Bruker Daltonics</li><br />
<br />
<li> [https://www.biomerieux.com/us/en/our-offer/clinical-products/vitek-ms-prime.html VITEK MS PRIME] MALDI-ToF mass spectrometry from bioMérieux for routine microbial identification (commercial)</li><br />
<br />
<li> [https://microbenet.cdc.gov/ MicrobeNet], a free online resource maintained by the Centers for Disease Control and Prevention (CDC, Atlanta, USA)</li><br />
<br />
<li> [https://spectrometrylab.wordpress.com/ Open Source Spectrometry] - Matthias Mailänder's Blog (OpenChrom, Lablicate)</li><br />
<br />
<li> [https://maldi-up.ua-bw.de/index.asp MALDI-UP] - a free catalogue enabling the exchange of MALDI-TOF-MS spectra between users working in the field of microbiology, food analytics and in other fields, hosted at the CVUA Stuttgart</li><br />
<br />
<li> [https://www.longdom.org/open-access/biospean-a-freeware-tool-for-processing-spectra-from-maldi-intact-cellspore-mass-spectrometry-33447.html Biospean] - a freeware tool for processing spectra from MALDI intact cell/spore mass spectrometry</li><br />
<br />
<li> [https://idbac.org/ IDBac] - a place to ID bacteria, organize strain collections & ask research questions </li><br />
<br />
<li> [https://mabritec.com/en// Mabritec & Mabriteccentral] - a comprehensive ''in silico'' database as an attractive alternative for a fast, accurate and cost-effective germ identification.<br />
<br />
</ul><br />
<br />
<!-- externe MALDI Datenbanken und MPS Sammlungen--> <br />
<br />
<!-- chinesische Hersteller von MS Lösungen --> <br />
<br />
<!-- Andromas? --></div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Other_MALDI-ToF_MS_Ressources&diff=1129Other MALDI-ToF MS Ressources2026-03-08T10:43:10Z<p>Laschp: </p>
<hr />
<div>Below is a list of resources that may be useful for MALDI-ToF MS-based identification of bacteria. This list is not exhaustive and will be updated regularly. Please report outdated links.<br><br />
<br />
[[File:MALDI-workflow.png|500px|right|thumb|Workflow of microbial identification using MALDI-ToF MS (Copyright Peter Lasch, RKI Berlin, 2025)]]<br />
<br />
<ul><br />
<li> [https://www.bruker.com/en/applications/microbiology-and-diagnostics/microbiological-research/maldi-biotyper-for-microbial-research.html MALDI Biotyper] (MBT), a commercial solution for microbial research from Bruker Daltonics</li><br />
<br />
<li> [https://www.biomerieux.com/us/en/our-offer/clinical-products/vitek-ms-prime.html VITEK MS PRIME] MALDI-ToF mass spectrometry from bioMérieux for routine microbial identification (commercial)</li><br />
<br />
<li> [https://microbenet.cdc.gov/ MicrobeNet], a free online resource maintained by the Centers for Disease Control and Prevention (CDC, Atlanta, USA)</li><br />
<br />
<li> [https://spectrometrylab.wordpress.com/ Open Source Spectrometry] - Matthias Mailänder's Blog (OpenChrom, Lablicate)</li><br />
<br />
<li> [https://maldi-up.ua-bw.de/index.asp MALDI-UP] - a free catalogue enabling the exchange of MALDI-TOF-MS spectra between users working in the field of microbiology, food analytics and in other fields, hosted at the CVUA Stuttgart</li><br />
<br />
<li> [https://www.longdom.org/open-access/biospean-a-freeware-tool-for-processing-spectra-from-maldi-intact-cellspore-mass-spectrometry-33447.html Biospean] - a freeware tool for processing spectra from MALDI intact cell/spore mass spectrometry</li><br />
<br />
<li> [https://idbac.org/ IDBac] - a place to ID bacteria, organize strain collections & ask research questions </li><br />
<br />
</ul><br />
<br />
<!-- externe MALDI Datenbanken und MSP Sammlungen--> <br />
<br />
<!-- chinesische Hersteller von MS Lösungen --> <br />
<br />
<!-- Andromas? --> <br />
<br />
<!-- Firma in Zürich? --><br />
<br />
<!-- Datenbank USA --></div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Other_MALDI-ToF_MS_Ressources&diff=1128Other MALDI-ToF MS Ressources2026-03-08T10:36:33Z<p>Laschp: </p>
<hr />
<div>Below is a list of resources that may be useful for MALDI-ToF MS-based identification of bacteria. This list is not exhaustive and will be updated regularly. Please report outdated links.<br><br />
<br />
[[File:MALDI-workflow.png|500px|right|thumb|Workflow of microbial identification using MALDI ToF MS (Copyright Peter Lasch, RKI Berlin, 2025)]]<br />
<br />
<ul><br />
<li> [https://www.bruker.com/en/applications/microbiology-and-diagnostics/microbiological-research/maldi-biotyper-for-microbial-research.html MALDI Biotyper] (MBT), a commercial solution for microbial research from Bruker Daltonics</li><br />
<br />
<li> [https://www.biomerieux.com/us/en/our-offer/clinical-products/vitek-ms-prime.html VITEK MS PRIME] MALDI-ToF mass spectrometry from bioMérieux for routine microbial identification (commercial)</li><br />
<br />
<li> [https://microbenet.cdc.gov/ MicrobeNet], a free online resource maintained by the Centers for Disease Control and Prevention (CDC, Atlanta, USA)</li><br />
<br />
<li> [https://spectrometrylab.wordpress.com/ Open Source Spectrometry] - Matthias Mailänder's Blog (OpenChrom, Lablicate)</li><br />
<br />
<li> [https://maldi-up.ua-bw.de/index.asp MALDI-UP] - a free catalogue enabling the exchange of MALDI-TOF-MS spectra between users working in the field of microbiology, food analytics and in other fields, hosted at the CVUA Stuttgart</li><br />
<br />
<li> [https://www.longdom.org/open-access/biospean-a-freeware-tool-for-processing-spectra-from-maldi-intact-cellspore-mass-spectrometry-33447.html Biospean] - a freeware tool for processing spectra from MALDI intact cell/spore mass spectrometry</li><br />
<br />
</ul><br />
<br />
<!-- externe MALDI Datenbanken und MSP Sammlungen--> <br />
<br />
<!-- chinesische Hersteller von MS Lösungen --> <br />
<br />
<!-- Andromas? --> <br />
<br />
<!-- Firma in Zürich? --><br />
<br />
<br />
<br />
<!-- Datenbank USA --></div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=Other_MALDI-ToF_MS_Ressources&diff=1127Other MALDI-ToF MS Ressources2026-03-08T10:36:03Z<p>Laschp: </p>
<hr />
<div>Below is a list of resources that may be useful for MALDI-ToF MS-based identification of bacteria. This list is not exhaustive and will be updated regularly. Please report outdated links.<br><br />
<br />
[[File:MALDI-workflow.png|600px|right|thumb|Workflow of microbial identification using MALDI ToF MS (Copyright Peter Lasch, RKI Berlin, 2025)]]<br />
<br />
<ul><br />
<li> [https://www.bruker.com/en/applications/microbiology-and-diagnostics/microbiological-research/maldi-biotyper-for-microbial-research.html MALDI Biotyper] (MBT), a commercial solution for microbial research from Bruker Daltonics</li><br />
<br />
<li> [https://www.biomerieux.com/us/en/our-offer/clinical-products/vitek-ms-prime.html VITEK MS PRIME] MALDI-ToF mass spectrometry from bioMérieux for routine microbial identification (commercial)</li><br />
<br />
<li> [https://microbenet.cdc.gov/ MicrobeNet], a free online resource maintained by the Centers for Disease Control and Prevention (CDC, Atlanta, USA)</li><br />
<br />
<li> [https://spectrometrylab.wordpress.com/ Open Source Spectrometry] - Matthias Mailänder's Blog (OpenChrom, Lablicate)</li><br />
<br />
<li> [https://maldi-up.ua-bw.de/index.asp MALDI-UP] - a free catalogue enabling the exchange of MALDI-TOF-MS spectra between users working in the field of microbiology, food analytics and in other fields, hosted at the CVUA Stuttgart</li><br />
<br />
<li> [https://www.longdom.org/open-access/biospean-a-freeware-tool-for-processing-spectra-from-maldi-intact-cellspore-mass-spectrometry-33447.html Biospean] - a freeware tool for processing spectra from MALDI intact cell/spore mass spectrometry</li><br />
<br />
</ul><br />
<br />
<!-- externe MALDI Datenbanken und MSP Sammlungen--> <br />
<br />
<!-- chinesische Hersteller von MS Lösungen --> <br />
<br />
<!-- Andromas? --> <br />
<br />
<!-- Firma in Zürich? --><br />
<br />
<br />
<br />
<!-- Datenbank USA --></div>Laschphttps://wiki-ms.microbe-ms.com/index.php?title=File:MALDI-workflow.png&diff=1126File:MALDI-workflow.png2026-03-08T10:34:29Z<p>Laschp: </p>
<hr />
<div></div>Laschp