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Hello. I worked with DESeq2 package for analyzing RNA sequencing results, but now I want to work with proteomics data and do some statistics on it and it is important for me to work with R. But I don't know where should I start and which package is suitable. Thanks.
Do you want to perform a differential expression analysis on your proteomics data? If so, an option within the bioconductor framework would be
msqrob2https://www.bioconductor.org/packages/release/bioc/html/msqrob2.html, which is from the group I'm working in.I'm not a proteomics expert myself, but I have heard of people using
limma (voom), which has not been developed specifically for proteomics data but has been extensively used for RNA-seq and microarray data as well. Other bioconductor packages I heard of in this context but never used myself areDEqMSandDEP(the differential testing of the latter builds on limma as well if I remember correctly).If you want limma (which is fine) then use the ‚traditional‘ limma pipeline, not voom. Voom is for digital sequencing data, not the intensity data returned by mass spec, nor for arrays.
Fair point. I was referring to this discussion Using limma for quantitative proteomics data, where at one point limma voom was suggested for the analysis of "quantitative proteomics data". The discussion is quite lengthy though, and not very well formatted, so I am not entirely sure what the end conclusion was.
I refer to several posts from the limma developer (e.g. voom for spectral counts) and others.
Thanks for the reference!