Amit Yadav - MassWiz: A Novel Scoring Algorithm with Target-Decoy Based Analysis Pipeline for Tandem Mass Spectrometry

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  Publication Details (including relevant citation   information):

  Amit Kumar Yadav, Dhirendra Kumar, and Debasis Dash*


  Institute of Genomics and Integrative   Biology (CSIR), Mall Road, Delhi, India

  J. Proteome Res., 2011, 10 (5), pp 2154–2160

  DOI: 10.1021/pr200031z

  Publication Date (Web): March 18, 2011

  Copyright © 2011 American Chemical Society


  Mass spectrometry has made rapid advances in the recent past and   has become the preferred method for proteomics. Although many   open source algorithms for peptide identification exist, such as   X!Tandem and OMSSA, it has majorly been a domain of proprietary   software. There is a need for better, freely available, and   configurable algorithms that can help in identifying the correct   peptides while keeping the false positives to a minimum. We have   developed MassWiz, a novel empirical scoring function that gives   appropriate weights to major ions, continuity of b-y ions,   intensities, and the supporting neutral losses based on the   instrument type. We tested MassWiz accuracy on 486,882 spectra   from a standard mixture of 18 proteins generated on 6 different   instruments downloaded from the Seattle Proteome Center public   repository. We compared the MassWiz algorithm with Mascot,   Sequest, OMSSA, and X!Tandem at 1% FDR. MassWiz outperformed all   in the largest data set (AGILENT XCT) and was second only to   Mascot in the other data sets. MassWiz showed good performance in   the analysis of high confidence peptides, i.e., those identified   by at least three algorithms. We also analyzed a yeast data set   containing 106,133 spectra downloaded from the NCBI Peptidome   repository and got similar results. The results demonstrate that   MassWiz is an effective algorithm for high-confidence peptide   identification without compromising on the number of assignments.   MassWiz is open-source, versatile, and easily configurable.

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