evaluate_filter {MSnID} | R Documentation |
Filter out peptide-to-spectrum MS/MS identifications.
evaluate_filter(object, filter, level=c("PSM", "peptide", "accession"))
object |
An instance of class "MSnID". |
filter |
Either an instance of MSnIDFilter class or a |
level |
Level at which the filter will be evaluated. Possible values are "PSM", "peptide" and "accession". Multiple are OK. Default is all of them. |
Returns a matrix with with column names "fdr" and "n". Column "n" contains the number of features (spectra, peptides or proteins/accessions) passing the filter. Column "fdr" is the false discovery rate (i.e. identification confidence) for the corresponding features. Row names correspond to the provided levels.
Vladislav A Petyuk vladislav.petyuk@pnnl.gov
data(c_elegans) ## Filtering using string: msnidObj <- assess_termini(msnidObj, validCleavagePattern="[KR]\\.[^P]") table(msnidObj$numIrregCleavages) evaluate_filter(msnidObj, "numIrregCleavages == 0") ## Filtering using filter object: # first adding columns that will be used as filters msnidObj$msmsScore <- -log10(msnidObj$`MS-GF:SpecEValue`) msnidObj$mzError <- abs(msnidObj$experimentalMassToCharge - msnidObj$calculatedMassToCharge) # setting up filter object filtObj <- MSnIDFilter(msnidObj) filtObj$msmsScore <- list(comparison=">", threshold=10.0) filtObj$mzError <- list(comparison="<", threshold=0.1) # 0.1 Thomson show(filtObj) evaluate_filter(msnidObj, filtObj)