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GDSCTools for mining pharmacogenomic interactions in cancer
Thomas Cokelaer, Elisabeth Chen, Francesco Iorio, Michael Menden, Howard Lightfoot, Julio Saez-Rodriguez, Mathew Garnett

GDSCTools for mining pharmacogenomic interactions in cancer

Science & Mathematics Published 2018 Verification Pending

Overview & Synopsis

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.

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Document Information

Document Title GDSCTools for mining pharmacogenomic interactions in cancer
Author / Organization Thomas Cokelaer, Elisabeth Chen, Francesco Iorio, Michael Menden, Howard Lightfoot, Julio Saez-Rodriguez, Mathew Garnett
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2018
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-252302
Original Source Link Visit Source Page on hal.science »