OpenMS
2.5.0
|
Calculates a distribution of the mass error from given mass spectra and IDs.
The command line parameters of this tool are:
IDMassAccuracy -- Calculates a distribution of the mass error from given mass spectra and IDs. Full documentation: http://www.openms.de/documentation/UTILS_IDMassAccuracy.html Version: 2.5.0-nightly-2020-03-06 Mar 7 2020, 01:22:16, Revision: 84b1398 To cite OpenMS: Rost HL, Sachsenberg T, Aiche S, Bielow C et al.. OpenMS: a flexible open-source software platform for mass spectrometry data analysis. Nat Meth. 2016; 13, 9: 741-748. doi:10.1038/nmeth.3959. Usage: IDMassAccuracy <options> Options (mandatory options marked with '*'): -in <file list>* Input mzML file list, containing the spectra. (valid formats: 'mzML') -id_in <file list>* Input idXML file list, containing the identifications. (valid formats : 'idXML') -out_precursor <file> Output file which contains the deviations from the precursors (valid formats: 'tsv') -precursor_error_ppm If this flag is used, the precursor mass tolerances are estimated in ppm instead of Da. -out_fragment <file> Output file which contains the fragment ion m/z deviations (valid formats: 'tsv') -fragment_error_ppm If this flag is used, the fragment mass tolerances are estimated in ppm instead of Da. -fragment_mass_tolerance <tolerance> Maximal fragment mass tolerance which is allowed for MS/MS spectra, used for the calculation of matching ions. (default: '0.5') Common UTIL options: -ini <file> Use the given TOPP INI file -threads <n> Sets the number of threads allowed to be used by the TOPP tool (defau lt: '1') -write_ini <file> Writes the default configuration file --help Shows options --helphelp Shows all options (including advanced)
INI file documentation of this tool:
Given a number of peak maps and for each of the maps an idXML file which contains peptide identifications the theoretical masses of the identifications and the peaks of the spectra are compared. This can be done for precursor information stored in the spectra as well as for fragment information.
The result is a distribution of errors of experimental vs. theoretical masses. Having such distributions given the search parameters of the sequence database search can be adjusted to speed-up the identification process and to get a higher performance.