12. Standalone application¶
Although we would encourage you to use the Python shell to have as much flexibility as possible, we also provide a standalone applications.
Currently, there are two standalones. The gdsctools_anova and gdsctools_regression. The first one is a pure Python implementation while the second one is snakemake-based.
12.1. gdsctools_anova application¶
called gdsctools_anova. This standalone application should be installed with GDSCTools automatically. It focuses on the ANOVA analysis only, and can be used to analysis one set of IC50 and genomic feature at a time.
You can obtain the help by typing:
The main goal is to provide an interface to the python library and consequently, one be able to redo the analysis as shown in the quickstart:
* One drug One Feature with figure(s) and HTMLs * One Drug All Feature with figure and HTMLs * All Drug All Feature with figures and HTMLs
We suppose the input data file is called IC50_10drugs.tsv
gdsctools_anova --input-ic50 IC50_10drugs.tsv --drug Drug_999_IC50 --feature TP53_mut --onweb
12.1.4. Some other settings¶
Again, you can use the
--help to get up-to-date information about the available
arguments. However, let us give a couple of interesting ones.
If you are interesting in a specific association of drug and feature, it is convenient to get the valid drug names:
or feature names:
By default the analysis is PANCAN (includes all tissues) but you can restrict the analysis to a set of tissues (or just one):
--tissues breast, cervix
To know the names of the tissues, use:
12.2. gdsctools_regression application¶
Let us consider the case where you have an IC50 file and a genomic file. The first step consists in preparing the working directory:
gdsctools_regression -I IC50_v17.csv.gz -F genomic_features_v17.csv.gz --method lasso -O lasso_analysis
On a local computer:
snakemake -s regression.rules -j 4
On a distributed-computing system using e.g SLURM framework, use:
srun --qos normal snakemake -s regression.rules -j 40 --cluster "sbatch --qos normal"