PharmacoGx: an R package for analysis of large pharmacogenomic datasets

Petr Smirnov, Zhaleh Safikhani, Nehme El-Hachem, Dong Wang, Adrian She, Catharina Olsen, Mark Freeman, Heather Selby, Deena M.A. Gendoo, Patrick Grossmann, Andrew H. Beck, Hugo J.W.L. Aerts, Mathieu Lupien, Anna Goldenberg, Benjamin Haibe-Kains

Research output: Contribution to journalArticlepeer-review

84 Citations (Scopus)


Summary: Pharmacogenomics holds great promise for the development of biomarkers of drug response and the design of new therapeutic options, which are key challenges in precision medicine. However, such data are scattered and lack standards for efficient access and analysis, consequently preventing the realization of the full potential of pharmacogenomics. To address these issues, we implemented PharmacoGx, an easy-to-use, open source package for integrative analysis of multiple pharmacogenomic datasets. We demonstrate the utility of our package in comparing large drug sensitivity datasets, such as the Genomics of Drug Sensitivity in Cancer and the Cancer Cell Line Encyclopedia. Moreover, we show how to use our package to easily perform Connectivity Map analysis. With increasing availability of drug-related data, our package will open new avenues of research for meta-analysis of pharmacogenomic data.Availability and implementation: PharmacoGx is implemented in R and can be easily installed on any system. The package is available from CRAN and its source code is available from GitHub.Contact: [email protected] or [email protected] information:Supplementary data are available at Bioinformatics online.
Original languageEnglish
Pages (from-to)1244-1246
Number of pages3
Issue number8
Early online date9 Dec 2015
Publication statusPublished - 15 Apr 2016


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