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Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform.
Yu, Fengchao; Teo, Guo Ci; Kong, Andy T; Fröhlich, Klemens; Li, Ginny Xiaohe; Demichev, Vadim; Nesvizhskii, Alexey I.
Affiliation
  • Yu F; Department of Pathology, University of Michigan, Ann Arbor, MI, USA. yufe@umich.edu.
  • Teo GC; Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
  • Kong AT; Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
  • Fröhlich K; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
  • Li GX; Proteomics Core Facility, Biozentrum, University of Basel, Basel, Switzerland.
  • Demichev V; Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
  • Nesvizhskii AI; Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Nat Commun ; 14(1): 4154, 2023 07 12.
Article in En | MEDLINE | ID: mdl-37438352
ABSTRACT
Liquid chromatography (LC) coupled with data-independent acquisition (DIA) mass spectrometry (MS) has been increasingly used in quantitative proteomics studies. Here, we present a fast and sensitive approach for direct peptide identification from DIA data, MSFragger-DIA, which leverages the unmatched speed of the fragment ion indexing-based search engine MSFragger. Different from most existing methods, MSFragger-DIA conducts a database search of the DIA tandem mass (MS/MS) spectra prior to spectral feature detection and peak tracing across the LC dimension. To streamline the analysis of DIA data and enable easy reproducibility, we integrate MSFragger-DIA into the FragPipe computational platform for seamless support of peptide identification and spectral library building from DIA, data-dependent acquisition (DDA), or both data types combined. We compare MSFragger-DIA with other DIA tools, such as DIA-Umpire based workflow in FragPipe, Spectronaut, DIA-NN library-free, and MaxDIA. We demonstrate the fast, sensitive, and accurate performance of MSFragger-DIA across a variety of sample types and data acquisition schemes, including single-cell proteomics, phosphoproteomics, and large-scale tumor proteome profiling studies.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Proteomics / Tandem Mass Spectrometry Type of study: Prognostic_studies Language: En Journal: Nat Commun Journal subject: BIOLOGIA / CIENCIA Year: 2023 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Proteomics / Tandem Mass Spectrometry Type of study: Prognostic_studies Language: En Journal: Nat Commun Journal subject: BIOLOGIA / CIENCIA Year: 2023 Type: Article Affiliation country: United States