4.7 Article

DirecTag: Accurate sequence tags from peptide MS/MS through statistical scoring

Journal

JOURNAL OF PROTEOME RESEARCH
Volume 7, Issue 9, Pages 3838-3846

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/pr800154p

Keywords

sequence tagging; bioinformatics; de novo; multi-platform; peptide identification

Funding

  1. NIH [R01 CA126218, U24 CA126479, P30 ES000267]
  2. American Cancer Society Institutional Research [IRG-58-009-48]
  3. VICC Discovery
  4. D.B.M [P50 GM076547]
  5. NATIONAL CANCER INSTITUTE [R01CA126218, U24CA126479] Funding Source: NIH RePORTER
  6. NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES [P30ES000267] Funding Source: NIH RePORTER
  7. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [P50GM076547] Funding Source: NIH RePORTER

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In shotgun proteomics, tandem mass spectra of peptides are typically identified through database search algorithms such as Sequest. We have developed DirecTag, an open-source algorithm to infer partial sequence tags directly from observed fragment ions. This algorithm is unique in its implementation of three separate scoring systems to evaluate each tag on the basis of peak intensity, m/z fidelity, and complementarity. In data sets from several types of mass spectrometers, DirecTag reproducibly exceeded the accuracy and speed of InsPecT and GutenTag, two previously published algorithms for this purpose. The source code and binaries for DirecTag are available from http://fenchurch.mc.vanderbilt.edu.

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