A novel algorithm for validating peptide identification from a shotgun proteomics search engine

Ling Jian, Xinnan Niu, Zhonghang Xia, Parimal Samir, Chiranthani Sumanasekera, Zheng Mu, Jennifer L. Jennings, Kristen L. Hoek, Tara Allos, Leigh M. Howard, Kathryn M. Edwards, P. Anthony Weil, Andrew J. Link

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has revolutionized the proteomics analysis of complexes, cells, and tissues. In a typical proteomic analysis, the tandem mass spectra from a LC-MS/MS experiment are assigned to a peptide by a search engine that compares the experimental MS/MS peptide data to theoretical peptide sequences in a protein database. The peptide spectra matches are then used to infer a list of identified proteins in the original sample. However, the search engines often fail to distinguish between correct and incorrect peptides assignments. In this study, we designed and implemented a novel algorithm called De-Noise to reduce the number of incorrect peptide matches and maximize the number of correct peptides at a fixed false discovery rate using a minimal number of scoring outputs from the SEQUEST search engine. The novel algorithm uses a three-step process: data cleaning, data refining through a SVM-based decision function, and a final data refining step based on proteolytic peptide patterns. Using proteomics data generated on different types of mass spectrometers, we optimized the De-Noise algorithm on the basis of the resolution and mass accuracy of the mass spectrometer employed in the LC-MS/MS experiment. Our results demonstrate De-Noise improves peptide identification compared to other methods used to process the peptide sequence matches assigned by SEQUEST. Because De-Noise uses a limited number of scoring attributes, it can be easily implemented with other search engines.

Original languageEnglish (US)
Pages (from-to)1108-1119
Number of pages12
JournalJournal of Proteome Research
Issue number3
StatePublished - Mar 2013
Externally publishedYes


  • bioinformatics
  • database search engine
  • mass spectrometry
  • peptide spectrum match
  • proteomics
  • support vector machines
  • validation

ASJC Scopus subject areas

  • General Chemistry
  • Biochemistry


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