https://github.com/menchelab/sa_bone_marrow_scrnaseq

scRNA-seq analysis for Radhouani et al, Science Immunology, 2025.
https://github.com/menchelab/sa_bone_marrow_scrnaseq

Last synced: about 1 year ago
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scRNA-seq analysis for Radhouani et al, Science Immunology, 2025.

• Host: GitHub
• URL: https://github.com/menchelab/sa_bone_marrow_scrnaseq
• Owner: menchelab
• Created: 2023-07-16T14:20:38.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2025-01-19T09:34:34.000Z (over 1 year ago)
• Last Synced: 2025-02-05T20:01:54.697Z (over 1 year ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 88.3 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# SA_bone_marrow

scRNA-seq analysis for Radhouani et al. paper, Science Immunology, 2025.

The running order of the scripts is as follows:

1. Reading the data in R using:

   * R/1_read_in_pilot.Rmd

   * R/2_read_in_final.Rmd

2. Performing single-cell integration using scVI, initial annotation using scNym, and leiden clustering of mature and hematopoietic stem cells (HSC). 

   * python/1_scvi_integration.ipynb

   * python/2_scnym_annotation.ipynb

   * python/3_clustering_for_manual_annotation.ipynb

  

3. Marker detection of the clusters.

   * R/3_hvg_DEGs_HSC_scnym_annotation.Rmd

   * R/4_hvg_DEGs_mature_scnym_annotation.Rmd

  

These markers have been used for manual annotation of the clusters.

4. Transfer and plotting of the data with manually annotated clusters. This script relies on python/4_dynamo_cell_cycle.ipynb for cell cycle annotation.

   * python/5_transfering_manual_annotation.ipynb

   

5. Differential expression between SA- and PBS-treated mice across cell types.

   * R/5_DEGs_HSC_scnym_annotation_manual_annotation.Rmd

   * R/6_DEGs_mature_scnym_annotation_manual_annotation.Rmd

[![DOI](https://zenodo.org/badge/667063786.svg)](https://doi.org/10.5281/zenodo.14634569)