My project involves analyzing proteome of my sample. I have more than 100 samples for analysis. Would proteomic analysis in R help me? Is it better than other softwares?
I am assuming you are doing LC/MS/MS analysis. There are many software packages for proteomic analysis both pay and free. R and XCMS (which is written in R) are rather arcane packages since the manuals, if you can call them that, are pretty cryptic and many user adjustable parameters are poorly defined. The defaults almost never work properly. OpenMS and MZmine are more GUI-based with a little better online support (also free). The TransProteomePipeline is another good starting place. There are a myriad of decisions that you have to make along the way to an analysis. No method is idiot-proof, you need to understand what every method is doing and how each parameter setting is going to affect your PPV and FN prediction rates. Proteomic analysis is NOT for the faint of heart, it is more art that science. Anyone telling you otherwise is a fool.
Mr. Bhatia,
There should not have difference. These are statistics softwares.
I am assuming you are doing LC/MS/MS analysis. There are many software packages for proteomic analysis both pay and free. R and XCMS (which is written in R) are rather arcane packages since the manuals, if you can call them that, are pretty cryptic and many user adjustable parameters are poorly defined. The defaults almost never work properly. OpenMS and MZmine are more GUI-based with a little better online support (also free). The TransProteomePipeline is another good starting place. There are a myriad of decisions that you have to make along the way to an analysis. No method is idiot-proof, you need to understand what every method is doing and how each parameter setting is going to affect your PPV and FN prediction rates. Proteomic analysis is NOT for the faint of heart, it is more art that science. Anyone telling you otherwise is a fool.
Currently one of the better one's is: MSstats: by Vitek/Choi et al., and R package use them for free:
http://msstats.org/
Article MSstats: An R package for statistical analysis of quantitati...
and the tutorial here:https://www.youtube.com/watch?v=IYAqm2ENjkk
Thanks,
Biswa
I use custom R scripts all the time to explore the results of other database search engines like MSGF+(https://omics.pnl.gov/software/ms-gf). I find it helpful to plot various things like precursor error vs the spectral confidence score (colored by decoy vs target hits) to get a feel for the data at the PSM level. When I need to do statistical tests on label free quantification between samples I've used MaxQuant (http://www.coxdocs.org/doku.php?id=maxquant:start), it is written in R but has a GUI.
A free, well-documented, open source software for analysis of bottom-up proteomics in both Windows and linux environments is MetaMorpheus. Release versions can be found on GitHub (https://github.com/smith-chem-wisc/MetaMorpheus). This software can do peptide identification, PTM discovery, spectral calibration and quantitative analysis. It is very fast and easy to use.
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