Closed alchemistmatt closed 5 years ago
This is fixed via commit https://github.com/PNNL-Comp-Mass-Spec/PPMErrorCharter/commit/9d32729499e79ba0a6883f99291af5b911a667cb
New results for MoTrPAC_Pilot_TMT_W_S1_01_12Oct17_Elm_AQ-17-09-02:
PPMErrorCharter.exe -I:MoTrPAC_Pilot_TMT_W_S1_01_12Oct17_Elm_AQ-17-09-02.mzid.gz -EValue:1E-10 -Python
PPMErrorCharter, version 1.2.7111.20545 (June 21, 2019)
Statistic Original Refined
MeanMassErrorPPM: 1.704 -0.103
MedianMassErrorPPM: 2.355 0.009
StDev(Mean): 5.759 8.354
StDev(Median): 5.795 8.355
PPM Window for 99%: 0 +/- 19.740 25.073
PPM Window for 99%: high: 19.740 25.073
PPM Window for 99%: low: -15.031 -25.054
Release 1.2.7111 includes an updated executable. https://github.com/PNNL-Comp-Mass-Spec/PPMErrorCharter/releases
Note: The mass errors shown above differ from those in Issue #1 most likely due to the use of a different FASTA file to search this data. David, please re-process your data using the updated PPMErrorCharterPython.exe and paste the results as a new comment on this issue.
Same results:
mono PPMErrorCharterPython.exe -I:/data/MoTrPAC_Pilot_TMT_W_S1_01_12Oct17_Elm_AQ-17-09-02.mzid -EValue:1E-10
PPMErrorCharter, version 1.2.7111.20545 (June 21, 2019)
Using options:
PSM results file: /data/MoTrPAC_Pilot_TMT_W_S1_01_12Oct17_Elm_AQ-17-09-02.mzid
Spec EValue threshold: 1.0E-10
PPM Error histogram bin size: 0.5
Generating plots with OxyPlot
Creating plots for "MoTrPAC_Pilot_TMT_W_S1_01_12Oct17_Elm_AQ-17-09-02.mzid"
Using fixed data file "/data/MoTrPAC_Pilot_TMT_W_S1_01_12Oct17_Elm_AQ-17-09-02_FIXED.mzML"
Loading data from the .mzid file
6,290 PSMs passed the filters
Loading data from MoTrPAC_Pilot_TMT_W_S1_01_12Oct17_Elm_AQ-17-09-02_FIXED.mzML
25% complete
54% complete
82% complete
Statistic Original Refined
MeanMassErrorPPM: 2.207 0.143
MedianMassErrorPPM: 2.035 -0.001
StDev(Mean): 2.961 2.941
StDev(Median): 2.966 2.944
PPM Window for 99%: 0 +/- 10.932 8.834
PPM Window for 99%: high: 10.932 8.833
PPM Window for 99%: low: -6.863 -8.834
Using data points with original and refined MassError between -0.2 and 0.2 Da
Using data points with original and refined PpmError between -50 and 50 ppm
Removed 0 out-of-range items from the original 6,290 items.
Assuming Python 3 is at /usr/bin/python3
/usr/bin/python3 /app/PPMErrorCharter_Plotter.py /data/MZRefinery_Plotting_Metadata.txt
Reading metadata file: /data/MZRefinery_Plotting_Metadata.txt
Reading MoTrPAC_Pilot_TMT_W_S1_01_12Oct17_Elm_AQ-17-09-02_Histograms_TmpExportData.txt
Reading MoTrPAC_Pilot_TMT_W_S1_01_12Oct17_Elm_AQ-17-09-02_MassErrorsVsTime_TmpExportData.txt
Reading MoTrPAC_Pilot_TMT_W_S1_01_12Oct17_Elm_AQ-17-09-02_MassErrorsVsMass_TmpExportData.txt
Output: MoTrPAC_Pilot_TMT_W_S1_01_12Oct17_Elm_AQ-17-09-02_MZRefinery_Histograms.png
Plot "Mass error (PPM)" vs. "Original: Counts"
87 data points
Mass error histogram created
Output: MoTrPAC_Pilot_TMT_W_S1_01_12Oct17_Elm_AQ-17-09-02_MZRefinery_MassErrors.png
Plot "Scan Time (minutes)" vs. "Original: Mass Error (PPM)" and
Plot "m/z" vs. "Original: Mass Error (PPM)"
6,290 data points
6,290 data points
Mass error trend plot created
Generated plots; see:
/data/MoTrPAC_Pilot_TMT_W_S1_01_12Oct17_Elm_AQ-17-09-02/MoTrPAC_Pilot_TMT_W_S1_01_12Oct17_Elm_AQ-17-09-02_Histograms.png
and
/data/MoTrPAC_Pilot_TMT_W_S1_01_12Oct17_Elm_AQ-17-09-02/MoTrPAC_Pilot_TMT_W_S1_01_12Oct17_Elm_AQ-17-09-02_MassErrors.png
Processing completed successfully
The mass errors shown in issue #1 are incorrect (they are far too large). For example