iMetaLab Suite: A one‐stop toolset for metaproteomics

Metaproteomics is a recently thriving technique that studies the collection of proteins in complex microbiomes of the human, animal, plant, and environment. The bioinformatics workflow required for metaproteomics research, from the database search and protein quantification to downstream functional...

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Veröffentlicht in:iMeta 2022-06, Vol.1 (2), p.e25-n/a
Hauptverfasser: Li, Leyuan, Ning, Zhibin, Cheng, Kai, Zhang, Xu, Simopoulos, Caitlin M. A., Figeys, Daniel
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Sprache:eng
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Zusammenfassung:Metaproteomics is a recently thriving technique that studies the collection of proteins in complex microbiomes of the human, animal, plant, and environment. The bioinformatics workflow required for metaproteomics research, from the database search and protein quantification to downstream functional and taxonomic analysis has been challenging and thus limiting the accessibility of metaproteomics to microbiome researchers. To overcome these challenges, we have developed a set of tools named iMetaLab Suite. iMetaLab Suite includes the following components: (1) MetaLab Desktop, an automated database search software that facilities proteins identification and quantitation from microbiomes; (2) the automated iMetaReport that allows users to quickly access database search results and data set profiles; and (3) an interactive online toolset, iMetaShiny, covering most frequently used functional, taxonomic, and statistical analysis in metaproteomics. iMetaLab Suite is a free, easily accessible, and actively updated toolset available to assist researchers to explore metaproteomic data. Highlights A one‐stop solution for metaproteomics data analysis for nonexpert. Database search and result reports that include taxonomy and function. Interactive tools for frequently used metaproteomics data analysis tools. A one‐stop solution for metaproteomics data analysis for nonexpert, database search and result reports that include taxonomy and function, interactive tools for frequently used metaproteomics data analysis tools.
ISSN:2770-596X
2770-5986
2770-596X
DOI:10.1002/imt2.25