MMDRP: Drug Response Prediction and Biomarker Discovery Using Multi-Modal Deep Learning

MMDRP is now published in Bioinformatics Advances! (Open Access)

This repository contains preprocessing, training and evaluation code for MMDRP models.

Preprocessing

Training data was obtained from the following:

• CTRPv2 was obtained and processed using the PharmacoGx BioConductor package (https://bioconductor.org/packages/release/bioc/html/PharmacoGx.html)
  • Please refer to the R/01_Dose-Response_Data_Preparation.R file for details.
• DepMap Portal (https://depmap.org/portal/) for cell line profiling data.
  • 20Q2 for Protein Quantification data (lastest) and 21Q2 for mutational, gene expression, CNV, miRNA, metabolomics, histone, and RPPA data.
  • Please refer to the R/02_Omic_Data_Preparation.R file for details.

Training

Training was done in Python using the Pytorch framework. .py files are available in the src folder.
drp_full_model.pyis the main file used for training which can be run as a commandline program. Please refer to this file for the list of input arguments and their defaults.

Evaluation

Evaluation was performed using multiple cross-validation schemes. The predictions from the validation sets were then aggregated for each model, and further analyzed and compared in the 05_All_Comparison_Plots.R file.