Computing Exact p-values for a Cross-correlation Shotgun Proteomics Score Function

Abstract

The core of every protein mass spectrometry analysis pipeline is a function that assesses the quality of a match between an observed spectrum and a candidate peptide. We describe a procedure for computing exact p-values for the oldest and still widely used score function, SEQUEST XCorr. The procedure uses dynamic programming to enumerate efficiently the full distribution of scores for all possible peptides whose masses are close to that of the spectrum precursor mass. Ranking identified spectra by p-value rather than XCorr significantly reduces variance because of spectrum-specific effects on the score. In combination with the Percolator postprocessor, the XCorr p-value yields more spectrum and peptide identifications at a fixed false discovery rate than Mascot, X!Tandem, Comet, and MS-GF؉ across a variety of data sets. Molecular & Cellular

A Deeper Look into Comet—Implementation and Features

“…In 2008, a method to calculate the cross-correlation score in an efficient manner was published[16], where each experimental spectrum was preprocessed in a way that allows the cross-correlation score to be calculated by simply summing up processed intensity values at each theoretical fragment ion mass location. This optimization enabled the cross-correlation score to be applied to scoring all peptides instead of just the 500 best candidate peptides in the original implementation, enabling E-value[9] and p-value[17, 18] calculations based on the cross-correlation score distribution. Performance comparisons of Comet with other search engines can be found in [1] and [2] and a comparison of Comet vs. SEQUEST cross-correlation scores is presented below.…”

Progressive Calibration and Averaging for Tandem Mass Spectrometry Statistical Confidence Estimation: Why Settle for a Single Decoy?

“…However, our approach is different because it does not assume a specific parametric family [15, 16] or require the introduction of a new score function [14, 9]. These previous approaches are less general, and in some cases they might partially fail [12], In contrast, our approach is generally applicable, albeit at a computational cost.…”

“…Until recently, no such p-values were computed in the PSM context. Moreover, while considerable effort has of late been invested in computing such p-values [14, 1, 9, 15, 16, 12], we recently showed that there are further subtle but fundamental differences between the MHT context and the PSM one, implying that we typically cannot use FDR controlling procedures that were designed for the MHT context [? ].…”

Multiplexed Post-Experimental Monoisotopic Mass Refinement (mPE-MMR) to Increase Sensitivity and Accuracy in Peptide Identifications from Tandem Mass Spectra of Cofragmentation

“…When poorly calibrated scores (e.g., SEQUEST Xcorr) are used, including spectra with high charge states, this decreases the number of identifications. 33 …”