This repository contains the pipeline and a collection of scripts for analyzing non-COVID scRNA-seq samples and their corresponding control datasets described in the referenced article: Maatz, H., Lindberg, E.L., Adami, E. et al. The cellular and molecular cardiac tissue responses in human inflammatory cardiomyopathies after SARS-CoV-2 infection and COVID-19 vaccination. Nat Cardiovasc Res 4, 330–345 (2025).
The main goal of this project is to compare patterns of differential gene expression between control samples from different studies to better understand their behavior and potential biological differences.
The repository includes:
- scripts for preprocessing and generating count matrices from BAM files,
- a pipeline for differential gene expression analysis in scRNA-seq data,
- file with consistent versions of programs and applications which were used.
This project was developed as part of a comparative study focused on differences in gene expression between various control datasets to ensure a more consistent interpretation of single-cell analysis results.
Raw data is available via European Genome-Phenome Archive: https://ega-archive.org/studies/EGAS50000000769