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SWATH2stats: An R/Bioconductor Package to Process and Convert Quantitative SWATH-MS Proteomics Data for Downstream Analysis Tools

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  • Peter Blattmann
  • Moritz Heusel
  • Ruedi Aebersold

Abstract

SWATH-MS is an acquisition and analysis technique of targeted proteomics that enables measuring several thousand proteins with high reproducibility and accuracy across many samples. OpenSWATH is popular open-source software for peptide identification and quantification from SWATH-MS data. For downstream statistical and quantitative analysis there exist different tools such as MSstats, mapDIA and aLFQ. However, the transfer of data from OpenSWATH to the downstream statistical tools is currently technically challenging. Here we introduce the R/Bioconductor package SWATH2stats, which allows convenient processing of the data into a format directly readable by the downstream analysis tools. In addition, SWATH2stats allows annotation, analyzing the variation and the reproducibility of the measurements, FDR estimation, and advanced filtering before submitting the processed data to downstream tools. These functionalities are important to quickly analyze the quality of the SWATH-MS data. Hence, SWATH2stats is a new open-source tool that summarizes several practical functionalities for analyzing, processing, and converting SWATH-MS data and thus facilitates the efficient analysis of large-scale SWATH/DIA datasets.

Suggested Citation

  • Peter Blattmann & Moritz Heusel & Ruedi Aebersold, 2016. "SWATH2stats: An R/Bioconductor Package to Process and Convert Quantitative SWATH-MS Proteomics Data for Downstream Analysis Tools," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-7, April.
    • Handle: RePEc:plo:pone00:0153160
    DOI: 10.1371/journal.pone.0153160
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    Cited by:

    1. Martin Mehnert & Rodolfo Ciuffa & Fabian Frommelt & Federico Uliana & Audrey Drogen & Kilian Ruminski & Matthias Gstaiger & Ruedi Aebersold, 2020. "Multi-layered proteomic analyses decode compositional and functional effects of cancer mutations on kinase complexes," Nature Communications, Nature, vol. 11(1), pages 1-18, December.

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