GDSCTools for mining pharmacogenomic interactions in cancer

Thomas Cokelaer (1) , Elisabeth Chen (2) , Francesco Iorio (3) , Michael Menden (4) , Howard Lightfoot (2) , Julio Saez-Rodriguez (3, 5) , Mathew Garnett (2)

1 Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB
2 The Wellcome Trust Sanger Institute [Cambridge]
3 EMBL-EBI - European Bioinformatics Institute [Hinxton]
4 AstraZeneca
5 RWTH - Rheinisch-Westfälische Technische Hochschule Aachen University

Motivation: Large pharmacogenomic screenings integrate heterogeneous cancer genomic datasets as well as anti-cancer drug responses on thousand human cancer cell lines. Mining this data to identify new therapies for cancer sub-populations would benefit from common data structures, modular computational biology tools and user-friendly interfaces. Results: We have developed GDSCTools: a software aimed at the identification of clinically relevant genomic markers of drug response. The Genomics of Drug Sensitivity in Cancer (GDSC) database (www.cancerRxgene.org) integrates heterogeneous cancer genomic datasets as well as anti-cancer drug responses on a thousand cancer cell lines. Including statistical tools (analysis of variance) and predictive methods (Elastic Net), as well as common data structures, GDSCTools allows users to reproduce published results from GDSC and to implement new analytical methods. In addition, non-GDSC data resources can also be analysed since drug responses and genomic features can be encoded as CSV files.

Domaines: Cancer; Sciences pharmaceutiques

Thomas Cokelaer, Elisabeth Chen, Francesco Iorio, Michael Menden, Howard Lightfoot, et al.. GDSCTools for mining pharmacogenomic interactions in cancer. Bioinformatics, 2018, 34 (7), pp.1226-1228. ⟨10.1093/bioinformatics/btx744⟩. ⟨pasteur-03111932⟩