Please download the pbta-gene-expression-kallisto.stranded.rds data from OpenPBTA to data/ directory. Instructions on how to download the dataset are here.
How to run the code.
- Run
src/create_raw_files.pyfile to generate node and edge_list files. - Run
src/main.pyto generate the node embedding. This code is a based on metapath2vec paper.pytorch_geometrichas incorporated the methodology here.metapath2vecis an approach based on unweighted edges. Our proposed approach generalizes this to weighted networks.
- Please use the
--use_weightflag to run weighted Deep Walk. Weighted deep walk is slow. Therefore, the ideal approach is to run the unweighted approach first and then fine tune the embedding by using the weighted approach. - Please use the
--helpflag to see the command line arguments available.
- To visualize the generated embedding please use projetor.tensorflow.org.