title: MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics.
abstract: There is a need to better understand and handle the 'dark matter' of proteomics-the vast diversity of post-translational and chemical modifications that are unaccounted in a typical mass spectrometry-based analysis and thus remain unidentified. We present a fragment-ion indexing method, and its implementation in peptide identification tool MSFragger, that enables a more than 100-fold improvement in speed over most existing proteome database search tools. Using several large proteomic data sets, we demonstrate how MSFragger empowers the open database search concept for comprehensive identification of peptides and all their modified forms, uncovering dramatic differences in modification rates across experimental samples and conditions. We further illustrate its utility using protein-RNA cross-linked peptide data and using affinity purification experiments where we observe, on average, a 300% increase in the number of identified spectra for enriched proteins. We also discuss the benefits of open searching for improved false discovery rate estimation in proteomics.
authors.affiliation: Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.|Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA.
authors.forename: Andy T
authors.initials: AT
authors.lastname: Kong
authors.affiliation: Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA.
authors.forename: Felipe V
authors.identifier: http://orcid.org/0000-0002-8228-5374
authors.initials: FV
authors.lastname: Leprevost
authors.affiliation: Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA.
authors.forename: Dmitry M
authors.initials: DM
authors.lastname: Avtonomov
authors.affiliation: Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA.
authors.forename: Dattatreya
authors.identifier: http://orcid.org/0000-0001-8221-7673
authors.initials: D
authors.lastname: Mellacheruvu
authors.affiliation: Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.|Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA.
authors.forename: Alexey I
authors.identifier: http://orcid.org/0000-0002-2806-7819
authors.initials: AI
authors.lastname: Nesvizhskii
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000295:instrumentation / Q000379:methods*; D030562:Databases, Protein; D057809:HEK293 Cells; D006801:Humans; D010446:Peptide Fragments / Q000737:chemistry*; D011499:Protein Processing, Post-Translational; D020543:Proteome / Q000737:chemistry*; D040901:Proteomics / Q000295:instrumentation / Q000379:methods*; D053719:Tandem Mass Spectrometry / Q000379:methods*
chemical_list: D010446:Peptide Fragments; D020543:Proteome