pepFunk: a tool for peptide-centric functional analysis of metaproteomic human gut microbiome studies

Abstract Motivation Enzymatic digestion of proteins before mass spectrometry analysis is a key process in metaproteomic workflows. Canonical metaproteomic data processing pipelines typically involve matching spectra produced by the mass spectrometer to a theoretical spectra database, followed by mat...

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Veröffentlicht in:Bioinformatics 2020-08, Vol.36 (14), p.4171-4179
Hauptverfasser: Simopoulos, Caitlin M A, Ning, Zhibin, Zhang, Xu, Li, Leyuan, Walker, Krystal, Lavallée-Adam, Mathieu, Figeys, Daniel
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Sprache:eng
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Zusammenfassung:Abstract Motivation Enzymatic digestion of proteins before mass spectrometry analysis is a key process in metaproteomic workflows. Canonical metaproteomic data processing pipelines typically involve matching spectra produced by the mass spectrometer to a theoretical spectra database, followed by matching the identified peptides back to parent-proteins. However, the nature of enzymatic digestion produces peptides that can be found in multiple proteins due to conservation or chance, presenting difficulties with protein and functional assignment. Results To combat this challenge, we developed pepFunk, a peptide-centric metaproteomic workflow focused on the analysis of human gut microbiome samples. Our workflow includes a curated peptide database annotated with Kyoto Encyclopedia of Genes and Genomes (KEGG) terms and a gene set variation analysis-inspired pathway enrichment adapted for peptide-level data. Analysis using our peptide-centric workflow is fast and highly correlated to a protein-centric analysis, and can identify more enriched KEGG pathways than analysis using protein-level data. Our workflow is open source and available as a web application or source code to be run locally. Availability and implementation pepFunk is available online as a web application at https://shiny.imetalab.ca/pepFunk/ with open-source code available from https://github.com/northomics/pepFunk. Contact dfigeys@uottawa.ca Supplementary information Supplementary data are available at Bioinformatics online.
ISSN:1367-4803
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btaa289