MALDI Quality Tests - Revision history

Laschp: /* Quality test resolving power */

2025-05-29T06:42:07Z

Quality test resolving power

← Older revision		Revision as of 08:42, 29 May 2025
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	== Quality test ''resolving power'' ==		== Quality test ''resolving power'' ==

	The parameter ''resolving power'', as the ratio of the m/z position of a peak divided by its FWHM, is effectively a by-product of the procedure described in the previous paragraph. The resolving power of the QT indicates the average of values for specifically selected peaks found above the intensity threshold function. Note that to obtain the parameter ''resolving power'' only the 10 most intense peaks are utilized. A high resolving power, corresponding to low values of the FWHM, is thought to be beneficial for peak detection. Large FWHM values are determined in case of broad peak features, often in cases where high laser power has been applied, and may indicate sub-optimal settings when acquiring mass spectral data.<br>		The parameter ''resolving power'', as the ratio of the m/z position of a peak divided by its FWHM, is effectively a by-product of the procedure described in the previous paragraph. The resolving power of the QT indicates the average of values for specifically selected peaks found above the intensity threshold function values. Note that to obtain the parameter ''resolving power'' only the 10 most intense peaks are utilized. A high resolving power, corresponding to low values of the FWHM, is thought to be beneficial for peak detection. Large FWHM values are determined in case of broad peak features, often in cases where high laser power has been applied, and may indicate sub-optimal settings when acquiring mass spectral data.<br>
	Mean resolving power values between 200 and 1200 are assigned to test scores of 0 and 100, respectively, while the weighting factor equals 15% (0.15, standard settings).		Mean resolving power values between 200 and 1200 are assigned to test scores of 0 and 100, respectively, while the weighting factor equals 15% (0.15, standard settings).

Laschp: /* Baseline quality test */

2025-03-27T11:09:36Z

Baseline quality test

← Older revision		Revision as of 13:09, 27 March 2025
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	== Baseline quality test ==		== Baseline quality test ==

	Baseline deviation is calculated as the integral under the baseline curve. Prior to this, the spectrum is preprocessed, i.e. normalized (modified 2-norm algorithm) and offset corrected. This means that the procedure ultimately considers peak intensity values when normalizing MALDI-ToF mass spectra. From the preprocessed spectra a baseline curve is then obtained by the method ''baseline correction by asymmetric least squares'' (AsLS, see ref. below).<br>		Baseline deviation is calculated as the integral under the baseline curve. Prior to this, the spectrum is preprocessed, i.e. normalized (modified 1-norm algorithm) and offset corrected. This means that the procedure ultimately considers peak intensity values when normalizing MALDI-ToF mass spectra. From the preprocessed spectra a baseline curve is then obtained by the method ''baseline correction by asymmetric least squares'' (AsLS, see ref. below).<br>
	Baseline deviation values, i.e. areas under the baseline curve of intensity-normalized and offset corrected spectra, between 0.15 and 40, are assigned to baseline quality test scores of 100 and 0, respectively, while the baseline weighting factor is set to 20% (default parameters, values given are adjustable). Since the baselines can usually be well corrected by means of appropriate baseline correction routines such as AsLS, the weight of the baseline scores could be reduced below the default value (15%, i.e. 0.15). Note that the sum of all weightings should always equal 100% (or 1), otherwise an error message will be given.		Baseline deviation values, i.e. areas under the baseline curve of intensity-normalized and offset corrected spectra, between 0.15 and 40, are assigned to baseline quality test scores of 100 and 0, respectively, while the baseline weighting factor is set to 20% (default parameters, values given are adjustable). Since the baselines can usually be well corrected by means of appropriate baseline correction routines such as AsLS, the weight of the baseline scores could be reduced below the default value (15%, i.e. 0.15). Note that the sum of all weightings should always equal 100% (or 1), otherwise an error message will be given.

Laschp: /* Noise quality test */

2025-03-27T11:09:15Z

Noise quality test

← Older revision		Revision as of 13:09, 27 March 2025
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	* Initial baseline correction by an asymmetric least-square algorithm (AsLS)		* Initial baseline correction by an asymmetric least-square algorithm (AsLS)
	* Cutting the spectra between two m/z values, usually between m/z 2000 and 13000		* Cutting the spectra between two m/z values, usually between m/z 2000 and 13000
	* Normalization (modified 2-norm algorithm)		* Normalization (modified 1-norm algorithm)
	* Offset correction using the high m/z region to determine the spectrum offset value		* Offset correction using the high m/z region to determine the spectrum offset value
	The spectral noise is in the following determined by a complex algorithm that starts with removing very high and very low intensity values from the spectral vectors (top 30% and bottom 2% of intensity data). The data is then extensively smoothed by a Savitzky-Golay smoothing filter with 99 smoothing points. The smoothed data is subsequently subtracted from the intensity-adjusted spectrum vector. Finally, the standard deviation of the difference spectrum is determined to obtain the value of the absolute noise.<br>		The spectral noise is in the following determined by a complex algorithm that starts with removing very high and very low intensity values from the spectral vectors (top 30% and bottom 2% of intensity data). The data is then extensively smoothed by a Savitzky-Golay smoothing filter with 99 smoothing points. The smoothed data is subsequently subtracted from the intensity-adjusted spectrum vector. Finally, the standard deviation of the difference spectrum is determined to obtain the value of the absolute noise.<br>

Laschp: /* Useful links */

2025-03-27T10:40:55Z

Useful links

← Older revision		Revision as of 12:40, 27 March 2025
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	* Example of a HTML formatted quality test report: https://wiki.microbe-ms.com/uploads/report-quality-15-Dec-2024-11-17-18.html		* Example of a HTML formatted quality test report: https://wiki.microbe-ms.com/uploads/report-quality-15-Dec-2024-11-17-18.html
	* [[Description of MicrobeMS' main parameter file 'microbems.opt'\|Description of how to modify the default settings for quality testing by modifying the parameter file ''microbems.opt'']]		* [[Description of MicrobeMS' main parameter file 'microbems.opt'\|Description of how to modify the default settings for quality testing by modifying the parameter file ''microbems.opt'']]
	* [[~~Format_of_Quality_Test_Result_Files~~\|Description of the format of quality test result files (*.~~mat~~)]]		* [[Quality_Test_Result_Files\|Description of the format of quality test result files (MS Excel format, *.xls)]]

Laschp: /* Quality test resolving power */

2025-03-27T10:38:30Z

Quality test resolving power

← Older revision		Revision as of 12:38, 27 March 2025
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	== Quality test ''resolving power'' ==		== Quality test ''resolving power'' ==

	The parameter ''resolving power'', as the ratio of the m/z position of a peak divided by its FWHM, is effectively a by-product of the procedure described in the previous paragraph. The resolving power of the QT indicates the average of values for specifically selected peaks found above the intensity threshold function. To obtain the parameter ''resolving power'' only the 10 most intense peaks are utilized. A high resolving power, corresponding to low values of the FWHM, is thought to be beneficial for peak detection. Large FWHM values are determined in case of broad peak features, often in cases where high laser power has been applied, and may indicate sub-optimal settings when acquiring mass spectral data.<br>		The parameter ''resolving power'', as the ratio of the m/z position of a peak divided by its FWHM, is effectively a by-product of the procedure described in the previous paragraph. The resolving power of the QT indicates the average of values for specifically selected peaks found above the intensity threshold function. Note that to obtain the parameter ''resolving power'' only the 10 most intense peaks are utilized. A high resolving power, corresponding to low values of the FWHM, is thought to be beneficial for peak detection. Large FWHM values are determined in case of broad peak features, often in cases where high laser power has been applied, and may indicate sub-optimal settings when acquiring mass spectral data.<br>
	Mean resolving power values between 200 and 1200 are assigned to test scores of 0 and 100, respectively, while the weighting factor equals 15% (0.15, standard settings).		Mean resolving power values between 200 and 1200 are assigned to test scores of 0 and 100, respectively, while the weighting factor equals 15% (0.15, standard settings).

Laschp: /* Quality test resolving power */

2025-03-27T10:37:23Z

Quality test resolving power

← Older revision		Revision as of 12:37, 27 March 2025
Line 42:		Line 42:
	== Quality test ''resolving power'' ==		== Quality test ''resolving power'' ==

	The parameter ''resolving power'', as the ratio of the m/z position of a peak divided by its FWHM, is effectively a by-product of the procedure described in the previous paragraph. The resolving power of the QT indicates the average of values for peaks found above the intensity threshold function. A high resolving power, corresponding to low values of the FWHM, is thought to be beneficial for peak detection. Large FWHM values are determined in case of broad peak features, often in cases where high laser power has been applied, and may indicate sub-optimal settings when acquiring mass spectral data.<br>		The parameter ''resolving power'', as the ratio of the m/z position of a peak divided by its FWHM, is effectively a by-product of the procedure described in the previous paragraph. The resolving power of the QT indicates the average of values for specifically selected peaks found above the intensity threshold function. To obtain the parameter ''resolving power'' only the 10 most intense peaks are utilized. A high resolving power, corresponding to low values of the FWHM, is thought to be beneficial for peak detection. Large FWHM values are determined in case of broad peak features, often in cases where high laser power has been applied, and may indicate sub-optimal settings when acquiring mass spectral data.<br>
	Mean resolving power values between 200 and ~~800~~ are assigned to test scores of 0 and 100, respectively, while the weighting factor equals 25% (~~all in~~ standard settings).		Mean resolving power values between 200 and 1200 are assigned to test scores of 0 and 100, respectively, while the weighting factor equals 15% (0.15, standard settings).

	== Useful links ==		== Useful links ==

Laschp: /* Noise quality test */

2025-03-27T10:30:59Z

Noise quality test

← Older revision		Revision as of 12:30, 27 March 2025
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	* Normalization (modified 2-norm algorithm)		* Normalization (modified 2-norm algorithm)
	* Offset correction using the high m/z region to determine the spectrum offset value		* Offset correction using the high m/z region to determine the spectrum offset value
	~~Spectrum~~ noise is ~~then~~ determined as the ~~standard deviation~~ of the ~~pre~~-~~processed spectra~~, ~~with~~ the ~~top 20%~~ of the ~~intensity data, usually~~ the ~~peak data, removed~~.<br>		The spectral noise is in the following determined by a complex algorithm that starts with removing very high and very low intensity values from the spectral vectors (top 30% and bottom 2% of intensity data). The data is then extensively smoothed by a Savitzky-Golay smoothing filter with 99 smoothing points. The smoothed data is subsequently subtracted from the intensity-adjusted spectrum vector. Finally, the standard deviation of the difference spectrum is determined to obtain the value of the absolute noise.<br>
	Noise values between 0.2 and 6 are assigned to scores of 100 (great) and 0 (very poor), respectively, while the noise weighting factor is set to 30% (0.3, default settings).		Noise values between 0.2 and 6 are assigned to scores of 100 (great) and 0 (very poor), respectively, while the noise weighting factor is set to 30% (0.3, default settings).

Laschp: /* Introduction */

2025-03-27T10:04:02Z

Introduction

← Older revision		Revision as of 12:04, 27 March 2025
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	'''QT threshold 1 and 2 - what do these specifications mean'''? These specifications merely define the color coding of the QT results in the QT's HTML report. Test results with a score greater than QT threshold 2 are shown in green; scores lower than QT threshold 1 are shown in red. For all other QT results the color yellow is used in the HTML document (according to a traffic light scheme). It should be noted that predefined (default) color coding settings should not be interpreted in a strict sense. It is important to understand, that current standard QT settings are just suggestions chosen on the basis of testing MALDI-ToF MS data acquired at the Robert Koch Institute (RKI) over a long period of time. In these tests MALDI data from one MS instrument, an autofleX I mass spectrometer were analyzed. Mass data collected by other institutions that use alternative instruments may exhibit different spectrum characteristics. Furthermore, current QT parameter settings were chosen to assure the full dynamic range [0 100] of the scores. Therefore, it is quite possible that spectra with low (red) QT obtained by others can still be suitable for microbial identification analysis.<br>   <br>		'''QT threshold 1 and 2 - what do these specifications mean'''? These specifications merely define the color coding of the QT results in the QT's HTML report. Test results with a score greater than QT threshold 2 are shown in green; scores lower than QT threshold 1 are shown in red. For all other QT results the color yellow is used in the HTML document (according to a traffic light scheme). It should be noted that predefined (default) color coding settings should not be interpreted in a strict sense. It is important to understand, that current standard QT settings are just suggestions chosen on the basis of testing MALDI-ToF MS data acquired at the Robert Koch Institute (RKI) over a long period of time. In these tests MALDI data from one MS instrument, an autofleX I mass spectrometer were analyzed. Mass data collected by other institutions that use alternative instruments may exhibit different spectrum characteristics. Furthermore, current QT parameter settings were chosen to assure the full dynamic range [0 100] of the scores. Therefore, it is quite possible that spectra with low (red) QT obtained by others can still be suitable for microbial identification analysis.<br>   <br>

	'''Parameter ''number of bins'''''. Each QT produces as a result a specific test parameter. For example, the ''number of peaks'' test provides a specific numeric value, the ''number of peaks''. Such values have to be then converted into scores, with the highest score being assigned to spectra with equal or more than 80 peaks (current default setting, ~~see~~ screenshot ~~below~~). If fewer than 5 peaks are found, a score of 0 is given. For parameters between 5 and 80, intervals in the range of [~~5 80~~] are ~~used~~, on the basis of which the respective score values are then determined. The parameter ''number of bins'' specifies how many intervals are used by such an approach. To give an example, 9 bin limit values will be determined if the parameter ''number of bins'' equals 10. Bin limits will be determined in a log scale manner. Furthermore, it is obvious, that 9 bin limits are needed to define 10 bins. To stay with the example given above (''number of peaks''), the following interval, or bin limit values are automatically obtained: [~~5 7 10~~ 14 20 28 40 ~~57 80~~]). This means, that a QT score of 0 would be assigned if for example only 4 peaks would be determined from the mass spectrum under investigation. In case of 15 peaks a score of 44.4, of 43 peaks a score of 77.8, and of 70 peaks a QT score of 89.9 would be achieved, respectively.		'''Parameter ''number of bins'''''. Each QT produces as a result a specific test parameter. For example, the ''number of peaks'' test provides a specific numeric value, the ''number of peaks''. Such values have to be then converted into scores, with the highest score being assigned to spectra with equal or more than 70 peaks (current default setting, cf. screenshot). If fewer than 14 peaks are found, a score of 0 is given. For parameters between 14 and 70, intervals in the range of [14 70] are defined, on the basis of which the respective score values are then determined. The parameter ''number of bins'' specifies how many intervals are used by such an approach. To give an example, 14 bin limit values will be determined if the parameter ''number of bins'' equals 15. Bin limits will be determined in a log scale manner. Furthermore, it is obvious, that 14 bin limits are needed to define 15 bins. To stay with the example given above (''number of peaks''), the following interval, or bin limit values are automatically obtained: [14 16 19 22 25 28 32 36 40 45 50 56 63 70]). This means, that a QT score of 0 would be assigned if for example only 13 peaks would be determined from the mass spectrum under investigation. In case of 17 peaks a score of 14.3, of 28 peaks a score of 42.9, and of 69 peaks a QT score of 92.6 would be achieved, respectively.

	== Noise quality test ==		== Noise quality test ==

Laschp: /* Noise quality test */

2025-03-27T09:51:51Z

Noise quality test

← Older revision		Revision as of 11:51, 27 March 2025
Line 19:		Line 19:
	* Offset correction using the high m/z region to determine the spectrum offset value		* Offset correction using the high m/z region to determine the spectrum offset value
	Spectrum noise is then determined as the standard deviation of the pre-processed spectra, with the top 20% of the intensity data, usually the peak data, removed.<br>		Spectrum noise is then determined as the standard deviation of the pre-processed spectra, with the top 20% of the intensity data, usually the peak data, removed.<br>
	Noise values between 0.2 and 6 are assigned to scores of 100 (great) and 0 (very poor), respectively, while the noise weighting factor is set to 30% (0.3, default settings~~, see screenshot below~~).		Noise values between 0.2 and 6 are assigned to scores of 100 (great) and 0 (very poor), respectively, while the noise weighting factor is set to 30% (0.3, default settings).

	== Baseline quality test ==		== Baseline quality test ==

Laschp: /* Noise quality test */

2025-03-27T09:51:31Z

Noise quality test

← Older revision		Revision as of 11:51, 27 March 2025
Line 19:		Line 19:
	* Offset correction using the high m/z region to determine the spectrum offset value		* Offset correction using the high m/z region to determine the spectrum offset value
	Spectrum noise is then determined as the standard deviation of the pre-processed spectra, with the top 20% of the intensity data, usually the peak data, removed.<br>		Spectrum noise is then determined as the standard deviation of the pre-processed spectra, with the top 20% of the intensity data, usually the peak data, removed.<br>
	Noise values between 0.2 and 6 are assigned to scores of 100 (great) and 0 (very poor), respectively, while the noise weighting factor is set to 30% (default settings, see screenshot below).		Noise values between 0.2 and 6 are assigned to scores of 100 (great) and 0 (very poor), respectively, while the noise weighting factor is set to 30% (0.3, default settings, see screenshot below).

	== Baseline quality test ==		== Baseline quality test ==