Using R and Bioconductor for proteomics data analysis
Genomics
2014-01-14 v1
Abstract
This review presents how R, the popular statistical environment and programming language, can be used in the frame of proteomics data analysis. A short introduction to R is given, with special emphasis on some of the features that make R and its add-on packages a premium software for sound and reproducible data analysis. The reader is also advised on how to find relevant R software for proteomics. Several use cases are then presented, illustrating data input/output, quality control, quantitative proteomics and data analysis. Detailed code and additional links to extensive documentation are available in the freely available companion package RforProteomics.
Cite
@article{arxiv.1305.6559,
title = {Using R and Bioconductor for proteomics data analysis},
author = {Laurent Gatto and Andy Christoforou},
journal= {arXiv preprint arXiv:1305.6559},
year = {2014}
}