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Combining Results of Multiple Search Engines in Proteomics

期刊

MOLECULAR & CELLULAR PROTEOMICS
卷 12, 期 9, 页码 2383-2393

出版社

AMER SOC BIOCHEMISTRY MOLECULAR BIOLOGY INC
DOI: 10.1074/mcp.R113.027797

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资金

  1. NIGMS National Institutes of Health [R01 GM087221, R01-CA-126239, R01-GM-094231]
  2. American Recovery and Reinvestment Act (ARRA) funds [R01 HG005805]
  3. NHGRI
  4. NIGMS National Institutes of Health (Center for Systems Biology) [2P50 GM076547]
  5. National Science Foundation MRI [0923536]
  6. Luxembourg Centre for Systems Biomedicine
  7. University of Luxembourg
  8. Direct For Biological Sciences
  9. Div Of Biological Infrastructure [923536] Funding Source: National Science Foundation

向作者/读者索取更多资源

A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques.

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