This is the repository for the STAR protocols manuscript: Use of scREAD to Explore and Analyze Single-cell and Single-nucleus RNA-Seq data for Alzheimer’s Disease.
The protocol is baed on scREAD (single-cell RNA-Seq database for Alzheimer's Disease). It is a first-of-its-kind database to provide comprehensive analysis results of all the existing single-cell RNA-Seq and single-nucleus RNA-Seq data of Alzheimer's Disease in the public domain. The database is freely available at: http://osubmi.com/scread
The original scREAD paper was published in iScience: scREAD: A Single-Cell RNA-Seq Database for Alzheimer's Disease
If you have any questions or feedback regarding this notebook, please contact Cankun Wang cankun.wang@osumc.edu.
- Calculating overlapping DEGs from the same cell type across datasets (Optional section 6 in the manuscript)
- Run /overlapping_genes/overlap.rmd locally
- Use Google Colab version: https://colab.research.google.com/drive/1lInXa6jD4yc7RGJc0EWDfy5NNoXT1qye?usp=sharing
- Optional section 7: Running scREAD backend analysis workflow locally (Optional section 7 in the manuscript)
- open workflow readme
- overlapping_genes
- scread_db.rdata (91MB): scREAD dataset information, differential gene expression analysis results.
- overlap_functions.R: functions to obtain overlapping genes.
- overlap.rmd: R markdown version to calculate overlapping genes.
- workflow
- custom_marker.csv: A manually created marker gene list file used for identified cell types.
- functions.R: Visualization functions used in R.
- build_control_atlas.R: build control cells atlas Seurat object from count matrix file.
- transfer_cell_type.R: filter out control-like cells in disease dataset
- run_analysis.R: run analysis workflow, and export tables in scREAD database format.
- example_control.csv. The example control dataset.
- example_disease.csv. The example disease dataset.