ACE Mali 2026 scRNA-seq

Training materials for a hands-on single-cell RNA sequencing (scRNA-seq) tutorial, covering core analysis workflows with Seurat and automated cell type annotation using SingleR.

Author / Point of Contact

• Primary author: Colton McNinch, PhD
• Organization: Bioinformatics and Computational Biosciences Branch (BCBB), NIAID
• Contact: colton.mcninch@nih.gov

Dependencies and Acknowledgments

This project relies on several open-source R packages, including but not limited to:

• Seurat
• SingleR
• Bioconductor packages

We acknowledge and thank the developers and maintainers of these tools and the broader open-source community.

License

This project is released as government-developed work and is in the public domain.

Version Information

This is research/training software and does not follow a formal versioning scheme.
Updates may be made periodically to reflect improvements in methods or tools.

Setup (R environment with renv)

This project was developed using R 4.4.2.
For best results, use this version or as close as possible.

1. Clone or download this repository to your computer.

2. Open the project in RStudio by double-clicking the .Rproj file
   (this will automatically set the working directory to the correct location)

   OR set your working directory manually in R:

   setwd("path/to/your/downloaded/repository")

3. Install and restore the R environment:

   install.packages("renv")   # if not already installed
   renv::restore()

   If prompted to activate the project, choose 1.
   R may restart — after restarting, run renv::restore() again.

This will install all required packages with the exact versions specified in renv.lock.

Link to Video Recording

Online Recording