RWD-4-AD-Drugs

Using RWDs to generate AD drug repurposing hypotheses

Test Systems

Windows 10 PC, 16 GB memory, 500 GB hard disk, 6 GB NVIDIA GeForce GTX 1060 GPU Linux Ubuntu 18.04.2 LTS server, 62 GB memory, 500 GB hard disk, 11 GB GeForce RTX 2080 Ti GPU, and 16 CPU cores. Python environment install and activation Notes: recommend using tmux at the terminal to run all the following commands git clone https://github.com/calvin-zcx/RWD4Drug.git cd RWD4Drug/ conda env create -f environment.yml
conda activate rwd4drug

Code Structure

1. ipreprocess- EHR preorpcessing
2. iptw - High-throughput screening of AD by machine learning-based propensity-score reweighting method

shell commands are located in each package to run different functions