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Here I add two candidate modules for use in the PEP analysis engine. These should be investigated for efficacy in discrimination between correct and incorrect identifications.
MSFragger computes a hyperscore similar to that of X!:
hyperscore=log(Nb!Ny!∑i=1NbIb,i∑i=1NyIy,i)
where Nb is the number of matched b-ions, Ny is the number of matched y-ions, Ib,i are the intensities of matched b-ions, and Iy,i are the intensities of matched b-ions. While the theoretical fragment index can be adapted to include other fragment ion types, only b and y ions are included and used for scoring at this time. Expectation calculation is also performed in a similar manner as X! Tandem through linear regression of the survival function to estimate the expectation of a given hyperscore 51.
Nat Methods. Author manuscript; available in PMC 2017 Oct 10.
Published in final edited form as:
Nat Methods. 2017 May; 14(5): 513–520.
Published online 2017 Apr 10. doi: 10.1038/nmeth.4256
PMCID: PMC5409104
NIHMSID: NIHMS861287
PMID: 28394336
MSFragger: ultrafast and comprehensive peptide identification in shotgun proteomics
XCorr -
///
/// https://willfondrie.com/2019/02/an-intuitive-look-at-the-xcorr-score-function-in-proteomics/
///
/// A mass spectrum can be preprocessed by subtracting the mean intensities at all of the offsets.
/// Then a single dot product between the preprocessed mass spectrum and the theoretical peptide
/// mass spectrum yields the xcorr score, which is made possible because of the distributive
/// property of the dot product.
///
/// Since we have already chosen the match for this scan, we can use the matched ions to calculate the
/// xcorr and skip the dot product step.