In peterblattmann/SWATH2stats: Transform and Filter SWATH Data for Statistical Packages

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/"
)

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 exist both a release and development version of every Bioconductor R package.

Contribution

Please feel free to comment and post issues or pull requests on github (direct link in upper right corner).

Publication

The publication describing this package you can find here: 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

peterblattmann/SWATH2stats documentation built on July 2, 2023, 9:42 p.m.