scEPS

scEPS (single-cell Expression exPlainability Statistics)

This repo contains the code of the method, scEPS, for integrating GWAS and single-cell disease cell atlas data to identify disease-associated cell neighborhoods. scEPS calculates a $d$ statistic at each cell neighborhood, representing the difference between the variance in disease explained by variations in the expression of each GWAS vs. each mean-expression matched control gene. An illustration of the scEPS method is shown below:

Manual

We provide a detailed manual of scEPS in the Wiki page.

Installation

Option 1: using Anaconda or Miniforge

The easiest way to install scEPS is by creating a dedicated environment through Anaconda or Miniforge. To do this, please first install Anaconda or Miniforge on your machine. You may then install scEPS using the following commands:

git clone git@github.com:Genentech/sceps.git
cd sceps_tool
conda env create -f sceps.yml
conda activate sceps

Option 2: manually install required packages

The user may also manually install the required packages to run scEPS using the following commands:

conda install pandas=1.5.3
conda install numpy=1.26.2
conda install scipy=1.13.1
conda install scanpy=1.10.3
conda install anndata=0.10.7
conda install scikit-learn=1.3.2

Once the required packages to run scEPS are installed, the user may then install scEPS using:

git clone git@github.com:Genentech/sceps.git

Reference

The current draft of the manuscript is available here.