weiba / TSGCNN

Two-Space Graph Convolutional Neural Networks (TSGCNN)

TSGCNN code.

Requirements

• python==3.7.12
• pytorch==1.10.1
• numpy==1.21.5
• pandas==1.3.5
• Scimitar-learn==1.0.2
• pubchenpy==1.0.4

GDSC

• model.py: Code that implements the model.
• utils.py: The code that implements the tool.
• sampler.py: The code that implements the sampler.
• Directory New implements single-row and single-column zeroing experimental code.
• The directory Random implements the random zeroing experimental code.
• The directory Single implements the single drug experiment code.
• The directory Target implements the target drug experiment code.
• The directory processed_data contains the data required for the experiment.
  • cell_drg.csv records the log IC50 association matrix of cell line-drug.
  • cell_drugbinary.csv records the binary cell line-drug association matrix.
  • cellcna.csv records the CNA features of the cell line.
  • cell_gene.csv records cell line gene expression features.
  • cell_mutation.csv records somatic mutation features of cell lines.
  • drug_feature.csv records the fingerprint features of drugs.
  • null_mask.csv records the null values in the cell line-drug association matrix.
  • threshold.csv records the drug sensitivity threshold.

CCLE

Same as directory GDSC.

• CCLE/processed_data/
  • cell_drug.csv records the log IC50 association matrix of cell line-drug.
  • cell_drug_binary.csv records the binary cell line-drug association matrix.
  • cell_cna.csv records the CNA features of the cell line.
  • drug_feature.csv records the fingerprint features of drugs.
  • cell_gene.csv records cell line gene expression features.
  • cell_mutation.csv records somatic mutation features of cell lines.

Contact

If you have any question regard our code or data, please do not hesitate to open a issue or directly contact me ([e-mail]).