Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/30522
Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: mPies: a novel metaproteomics tool for the creation of relevant protein databases and automatized protein annotation
Author(s): Werner, Johannes
Géron, Augustin
Kerssemakers, Jules
Matallana-Surget, Sabine
Keywords: Bioinformatics
Metaproteomics
Microbial ecology
Protein annotation
Protein search database
Issue Date: Dec-2019
Citation: Werner J, Géron A, Kerssemakers J & Matallana-Surget S (2019) mPies: a novel metaproteomics tool for the creation of relevant protein databases and automatized protein annotation. Biology Direct, 14 (1), Art. No.: 21. https://doi.org/10.1186/s13062-019-0253-x
Abstract: Metaproteomics allows to decipher the structure and functionality of microbial communities. Despite its rapid development, crucial steps such as the creation of standardized protein search databases and reliable protein annotation remain challenging. To overcome those critical steps, we developed a new program named mPies (metaProteomics in environmental sciences). mPies allows the creation of protein databases derived from assembled or unassembled metagenomes, and/or public repositories based on taxon IDs, gene or protein names. For the first time, mPies facilitates the automatization of reliable taxonomic and functional consensus annotations at the protein group level, minimizing the well-known protein inference issue, which is commonly encountered in metaproteomics. mPies’ workflow is highly customizable with regards to input data, workflow steps, and parameter adjustment. mPies is implemented in Python 3/Snakemake and freely available on GitHub: https://github.com/johanneswerner/mPies/.
DOI Link: 10.1186/s13062-019-0253-x
Rights: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

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