GDSCTools

GDSCTools analyzes pharmacogenomic interactions by integrating heterogeneous cancer genomic datasets with anti-cancer drug response data from over a thousand human cancer cell lines to identify genomic markers predictive of drug sensitivity and resistance.

Key Features:

• Integration of Heterogeneous Data: Leverages the Genomics of Drug Sensitivity in Cancer (GDSC) database to combine diverse genomic datasets and drug response profiles from over a thousand human cancer cell lines.
• Modular Computational Tools: Provides modular computational biology tools to explore and validate clinically relevant genomic markers of drug response.
• Statistical and Predictive Methods: Implements analysis of variance (ANOVA) and Elastic Net regression for statistical testing and predictive modeling of drug–gene associations.
• Reproducibility and Extensibility: Enables reproduction of published results from the GDSC database and supports implementation of additional analytical methods.
• Support for External Data Resources: Accepts non‑GDSC datasets by encoding drug responses and genomic features as CSV files for analysis.

Scientific Applications:

• Identify Predictive Genomic Markers: Identify novel genomic markers that predict drug response to inform precision oncology research.
• Validate Drug Efficacy and Resistance Hypotheses: Validate hypotheses about drug efficacy and resistance mechanisms across diverse cancer cell lines.
• Stratify Cancer Sub-populations: Explore therapeutic avenues for specific cancer sub-populations through data-driven analysis.

Methodology:

Integration of GDSC genomic and drug-response datasets, application of analysis of variance (ANOVA) and Elastic Net regression for predictive modeling, and support for non‑GDSC inputs encoded as CSV files.