4.7 Article

FDRAnalysis: A Tool for the Integrated Analysis of Tandem Mass Spectrometry Identification Results from Multiple Search Engines

期刊

JOURNAL OF PROTEOME RESEARCH
卷 10, 期 4, 页码 2088-2094

出版社

AMER CHEMICAL SOC
DOI: 10.1021/pr101157s

关键词

bioinformatics; false discovery rate; multiple search engines; web server; data standards

资金

  1. BBSRC [BB/G010781/1, BB/F004605/1]
  2. Biotechnology and Biological Sciences Research Council [BB/G009058/1, BB/G010781/1, BB/F004605/1] Funding Source: researchfish
  3. BBSRC [BB/G009058/1, BB/G010781/1, BB/F004605/1] Funding Source: UKRI

向作者/读者索取更多资源

Confident identification of peptides via tandem mass spectrometry underpins modern high-throughput proteomics. This has motivated considerable recent interest in the postprocessing of search engine results to increase confidence and calculate robust statistical measures, for example through the use of decoy databases to calculate false discovery rates (FDR). FDR-based analyses allow for multiple testing and can assign a single confidence value for both sets and individual peptide spectrum matches (PSMs). We recently developed an algorithm for combining the results from multiple search I engines, integrating FDRs for sets of PSMs made by different search engine combinations. Here we describe a web-server and a downloadable application that makes this routinely available to the proteomics community. The web server offers a range of outputs including informative graphics to assess the confidence of the PSMs and any potential biases. The underlying pipeline also provides a basic protein inference step, integrating PSMs into protein ambiguity groups where peptides can be matched to more than one protein. Importantly, we have also implemented full support for the mzIdentML data standard, recently released by the Proteomics Standards Initiative, providing users with the ability to convert native formats to mzIdentML files, which are available to download.

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