All sources to reproduce paper results are available.
The following libraries and versions were used:
- Python 3.7.7
- pandas 1.0.5
- numpy 1.18.5
- networkx 2.4
- matplotlib 3.2.2
DiSCaGe has 3 options for use:
Type 1:
- Mutation data on MAF file format
- Gene interaction network in edge lists
Type 2:
- Binary mutation matrix
- Weighted mutation matrix
- Gene interaction network in edge lists
Type 3:
- Mutation score for each gene
- Gene interaction network in edge lists
A input file must be filled with data and the weights for each Variant_Classification. A running example is set on the file EXAMPLE_SNV_InDel_input_parameters.in, which is run using the follow command
python DiSCaGe.py EXAMPLE_SNV_InDel_input_parameters.in
A set of output files is generated. The final list of prioritized genes are found in file OUTPUT.score.mutatedGenes
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