Citation

Cokelaer et al. GDSCTools for mining pharmacogenomic interactions in cancer. Bioinformatics, 2017, https://doi.org/10.1093/bioinformatics/btx744

Note

Developed and tested for Python 2.7, 3.5, 3.6

Note

The GDSCTools libary works for Python 2.7 and 3.X but the standalone pipeline to be ran on cluster works on Python 3.X only (requires Snakemake).

Contributions

Please join https://github.com/CancerRxGene/gdsctools project

Documentation

On ReadTheDocs

GitHub

On github

Genomics of Drug Sensitivity in Cancer (GDSC) tools including pipelines related to http://www.cancerrxgene.org/

pip install gdsctools

For beginners, please visit the main documentation Installation section.

You will need 2 input matrices:

1. an IC50 matrix with COSMIC identifiers as rows and drugs as columns,
2. a genomic feature matrix with COSMIC identifiers as rows and features as columns.

Then, you can analyse the data with the standalone application:

gdsctools_anova --input-ic50 ic50.txt --input-features features.txt

or as a script:

from gdsctools import anova, ic50_test
an = ANOVA(ic50_test, features_filename)  # second arg is optional
an.anova_all()

More examples are provided in the documentation on ReadThedoc.

Note that first versions (ANOVA analysis) were based on https://github.com/francescojm/FI.GDSC.ANOVA repository. New tools have been added (regression based on Ridge, Lasso, OmniBEM tool, ...).