FIRE-mouse-2021-paper

This repository contains all of the code used to process and analyze the snRNA-seq data for Shabestari et al 2021.

pre-processing

We used the split-pipe pipeline to quantify gene expression in single-nuclei, check the split-pipe.sh script for the exact code.

primary processing

Next we performed quality control filtering, doublet detection, clustering, and data visualizations using Seurat and Scanpy in R and Python respectively. Check out the Processing.Rmd script for the code. Furthermore, for the analysis without the transplant conditions, check a very similar script Processing-4conditions.Rmd.

differential expression

We compared different conditions and identified marker genes using Seurat's differential gene expression platform, check out the following scripts: DEGs.Rmd and parallel_DEGs.R.

cell communication analysis

We performed cell-cell communications analysis using CellChat: cellchat.Rmd.

Co-expression network analysis

We used WGCNA to perform gene co-expression network analysis: scWGCNA.Rmd

Additional plotting:

Additional plotting code can be found here: plotting-for-paper.Rmd