PSC-scDRS

PSC-scDRS is designed to link scRNA-seq with polygenic disease risk at the single-cell resolution, independent of annotated cell types, and suggest drugs for the disease.

It provides comprehensive functionalities for:

• PSC-scDRS Identifying cells exhibiting excess expression across disease-associated genes implicated by Whole Exome Sequencing (WES).

In the Quick Start section, you can follow the instructions to install the requirements and run simple samples. To learn more about the functions, refer to the Documentations. Additionally, there, you can find detailed instructions on the data type and formats required as input for the PSC-scDRS function.

Table of contents

• Pipeline structure
• Quick Start
  • Prerequisites and Configuration
    • Custom configuration
  • Installing dependencies
  • Downloads
  • Data
  • Running PSC-scDRS

Pipeline Structure

Quick Start

Prerequisites and Configuration

PSC-scDRS requires significant computational resources. Ensure your system meets the following minimum requirements:

CPU: At least 16 cores.
RAM: At least 32 GB (e.g., scDRS may require up to 360 GB).

Note: For large datasets, it is recommended to run the pipeline on a high-performance computing (HPC) system.

Custom configuration

To fully utilize PSC-scDRS on an HPC or other systems, you must create a custom configuration file specifying:

Available CPU cores and memory. Scheduler settings (e.g., local or SLURM). Paths for reference databases. Please refer to the installation and configuration documentation for more details.

Downloads

Clone PSC-scDRS and install

All the codes and needed files for the sample file will be downloaded in this step.

1. Make a folder where you want to keep data and files for the PSC-scDRS project. For example, make a folder named PSC-scDRS in the home directory.

cd /home
mkdir -p PSC-scDRS

2. Clone the GitHub repo into that folder

cd /home/PSC-scDRS
git clone https://github.com/seirana/PSC-scDRS.git

3. If you get an error like “destination path 'PSC-scDRS' already exists”.

cd /home/PSC-scDRS
git pull --rebase origin main

Installing dependencies

PSC-scDRS needs some extra software to run:

step 1: Install scDRS

Pipeline will install it. If there is a problem, check their page.

step 2: Install the bcftools

Pipeline will install it. If there is a problem, check here.

step 3: Install MAGMA

This installation must be done manually.

Select and install the correct version for your operating system and desired genome reference from here.

This command installs Python libraries, scDRS, and bcftools.

cd /home/PSC-scDRS
bash setup_dependencies.sh

Data

Summary statistics of the GAISE single marker test on PSC whole-exome sequencing data are available as the sum_stat.zip file. It includes 'CHR' as the chromosome number and 'POS' as the position on the chromosome. 'MarkerID' contains chromosome number:position: major allele: minor allele, Allele1 is the major allele, and 'Allele2' is the minor allele, and 'p.value' is the p-value from the SAGIE single marker test.

The single-cell RNA sequencing data from the healthy human liver from the study by Andrews, T.S. et al. (PMID: 38199298) is provided as a sample dataset after applying the required modifications by the scDRS (PMID: 36050550) method.

Running PSC-scDRS

The pipeline will run the code smoothly.

cd /home/PSC-scDRS
bash PSC-scDRS_run.sh