4.7 Article

Tiered Human Integrated Sequence Search Databases for Shotgun Proteomics

期刊

JOURNAL OF PROTEOME RESEARCH
卷 15, 期 11, 页码 4091-4100

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.6b00445

关键词

shotgun mass spectrometry; search databases; human

资金

  1. National Institutes of Health from the National Institute of General Medical Sciences (NIGMS) [R01GM087221, 2P50GM076547]
  2. National Institute of Biomedical Imaging and Bioengineering [U54EB020406]
  3. NIEHS [U54ES017885]
  4. National Science Foundation MCB [1330912]
  5. EU FP7 'ProteomeXchange' [260558]
  6. Direct For Biological Sciences
  7. Div Of Molecular and Cellular Bioscience [1330912] Funding Source: National Science Foundation

向作者/读者索取更多资源

The results of analysis of shotgun proteomics mass spectrometry data can be greatly affected by the selection of the reference protein sequence database against which the spectra are matched. For many species there are multiple sources from which somewhat different sequence sets can be obtained. This can lead to confusion about which database is best in which circumstances-a problem especially acute in human sample analysis. All sequence databases are genome-based, with sequences for the predicted gene and their protein translation products compiled. Our goal is to create a set of primary sequence databases that comprise the union of sequences from many of the different available sources and make the result easily available to the community. We have compiled a set of four sequence databases of varying sizes, from a small database consisting of only the similar to 20,000 primary isoforms plus contaminants to a very large database that includes almost all nonredundant protein sequences from several sources. This set of tiered, increasingly complete human protein sequence databases suitable for mass spectrometry proteomics sequence database searching is called the Tiered Human Integrated Search Proteome set. In order to evaluate the utility of these databases, we have analyzed two different data sets, one from the HeLa cell line and the other from normal human liver tissue, with each of the four tiers of database complexity. The result is that approximately 0.8%, 1.1%, and 1.5% additional peptides can be identified for Tiers 2, 3, and 4, respectively, as compared with the Tier 1 database, at substantially increasing computational cost. This increase in computational cost may be worth bearing if the identification of sequence variants or the discovery of sequences that are not present in the reviewed knowledge base entries is an important goal of the study. We find that it is useful to search a data set against a simpler database, and then check the uniqueness of the discovered peptides against a more complex database. We have set up an automated system that downloads all the source databases on the first of each month and automatically generates a new set of search databases and makes them available for download at http://www.peptideatlas.org/thisp/.

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