| Citation: | Cokelaer et al. GDSCTools for mining pharmacogenomic interactions in cancer. Bioinformatics, 2017, https://doi.org/10.1093/bioinformatics/btx744 |
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| 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:
- an IC50 matrix with COSMIC identifiers as rows and drugs as columns,
- 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, ...).