Proteus is an R package for downstream analysis of MaxQuant output. The input for Proteus is the evidence file. Evidence data are aggregated into peptides and then into proteins. Proteus offers many visualisation and data analysis tools both at peptide and protein level. In particular it allows simple differential expression using limma.
Proteus is no longer under active development, and we believe that some of its features have become outdated. Specifically, we advise against using peptide and protein aggregation from the event file. Instead, we recommend importing the proteinGroups file directly into R and utilizing the maxLFQ normalization method. We would like to highlight that alternative protein quantification tools, such as Proteome Discoverer and Spectronaut, are available and offer normalized protein intensity data.
Proteus can be installed directly from GitHub. First, you need to install BioConductor and limma:
install.packages("BiocManager")
BiocManager::install()
BiocManager::install("limma")You also need devtools:
install.packages("devtools")In order to run examples or vignette code, additional packages with example data need to be installed:
devtools::install_github("bartongroup/proteusLabelFree")
devtools::install_github("bartongroup/proteusTMT")
devtools::install_github("bartongroup/proteusSILAC")Finally, you can install proteus:
devtools::install_github("bartongroup/Proteus", build_opts= c("--no-resave-data", "--no-manual"), build_vignettes=TRUE)Note: use build_vignettes = FALSE if you run into problems with vignettes installation.
Proteus contains tutorial vignettes. We suggest starting with the comprehensive tutorial for label-free proteomics:
vignette("proteus", package="proteus")There are additional, shorter vignettes, showing the specifics of using Proteus with TMT and SILAC data:
vignette("TMT", package="proteus")
vignette("SILAC", package="proteus")If, for some reason, you cannot build vignettes, copies are available online:
The article about this package can be found on BioRxiv.