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README.md
<!-- README.md is generated from README.Rmd. Please edit that file --> # SWATH2stats This package is intended to transform extracted SWATH/DIA data from the OpenSWATH or other (e.g. Spectronaut) software into a format directly-usable by statistics packages (e.g. mapDIA, PECA, MSstats) while performing filtering, annotation and FDR assessment if necessary. ## Analyzing SWATH/DIA data How to extract SWATH/DIA data before using SWATH2stats with OpenSWATH can be found here: <http://openswath.org> ## Usage SWATH2stats is a Bioconductor package. Go to <https://www.bioconductor.org/packages/release/bioc/html/SWATH2stats.html> to see all information related to installation. Importantly there exists both a release and development version. ## Contribution Please feel free to comment and post issues or pull requests on github. ## Publication For the publication describing this package, see: <https://doi.org/10.1371/journal.pone.0153160> ## References - Blattmann P, Heusel M, Aebersold R. SWATH2stats: An R/Bioconductor Package to Process and Convert Quantitative SWATH-MS Proteomics Data for Downstream Analysis Tools. PLoS ONE 11(4): e0153160 (2016). doi: 10.1371/journal.pone.0153160. - Rost HL, Rosenberger G, Navarro P, Gillet L, Miladinovic SM, Schubert OT, Wolski W, Collins BC, Malmstrom J, Malmstrom L, Aebersold R. OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data. Nature Biotechnology. 2014 Mar;32(3):219-23. doi: 10.1038/nbt.2841. - Choi M, Chang CY, Clough T, Broudy D, Killeen T, MacLean B, Vitek O. MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments.Bioinformatics. 2014 Sep 1;30(17):2524-6. doi: 10.1093/bioinformatics/btu305. - Rosenberger G, Ludwig C, Rost HL, Aebersold R, Malmstrom L. aLFQ: an R-package for estimating absolute protein quantities from label-free LC-MS/MS proteomics data. Bioinformatics. 2014 Sep 1;30(17):2511-3. doi: 10.1093/bioinformatics/btu200. - Suomi T., Corthals G., Nevalainen O.S., and Elo L.L. (2015). Using Peptide-Level Proteomics Data for Detecting Differentially Expressed Proteins. J Proteome Res. Nov 6;14(11):4564-70. doi: 10.1021/acs.jproteome.5b00363. - Suomi, T. and Elo L.L. (2017). Enhanced differential expression statistics for data-independent acquisition proteomics" Scientific Reports 7, Article number: 5869.doi:10.1038/s41598-017-05949-y