On the estimation of false positives in peptide identifications using decoy search strategy

Changyu Shen, Quanhu Sheng, Jie Dai, Yixue Li, Rong Zeng, Haixu Tang

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

False positive control/estimate in peptide identifications by MS is of critical importance for reliable inference at the protein level and downstream bioinformatics analysis. Approaches based on search against decoy databases have become popular for its conceptual simplicity and easy implementation. Although various decoy search strategies have been proposed, few studies have investigated their difference in performance. With datasets collected on a mixture of model proteins, we demonstrate that a single search against the target database coupled with its reversed version offers a good balance between performance and simplicity. In particular, both the accuracy of the estimate of the number of false positives and sensitivity is at least comparable to other procedures examined in this study. It is also shown that scrambling while preserving frequency of amino acid words can potentially improve the accuracy of false positive estimate, though more studies are needed to investigate the optimal scrambling procedure for specific condition and the variation ofthe estimate across repeated scrambling.

Original languageEnglish (US)
Pages (from-to)194-204
Number of pages11
JournalProteomics
Volume9
Issue number1
DOIs
StatePublished - Jan 1 2009

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Keywords

  • Decoy databases
  • False positive
  • Mass spectrometry
  • Peptides
  • Sensitivity

ASJC Scopus subject areas

  • Molecular Biology
  • Biochemistry

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