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scATAC‐seq Analysis Using R

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Ayushi Agrawal edited this page Feb 27, 2026 · 2 revisions

Description

This three-session, hands-on workshop provides an introduction to a typical single-cell ATAC-seq analysis and focuses on the data analysis steps to address unique computational challenges before the downstream analysis.

You’ll learn how to perform quality checks of raw data in the typical format provided by sequencing centers, how to process the data, perform dimensionality reduction for visualization, clustering and cell type annotation, generate a gene score matrix to identify cell types, perform motif and peak enrichment, differential chromatin accessibility analysis and jointly analyze multi-omic (expression and chromatin accessibility) data sets using ArchR.

Prior experience with transcriptomics data or attendance at an scRNA-seq or bulk RNA-seq workshop is required.

Note: Attendance at both sessions is highly recommended. The subsequent sessions build upon the previous ones.

Required experience:

  • Prior attendance at an scRNA-seq or bulk RNA-seq workshop, or experience with analysis of transcriptomics data
  • Familiarity with R and RStudio (e.g., reading in files, working with lists and dataframes)

Learning Path

Advanced   This is an advanced workshop building upon the RNA-Seq Analysis series. Prior experience with scRNA-seq or bulk RNA-seq is required. See introductory and intermediate workshops in the RNA-Seq Analysis series.

Materials

The slides are here.

  1. There is a zip file with code and data at this link.
  2. Open the link, press the download button (usually on the top right corner), and select “Direct Download” if a menu pops up.
  3. The zip file download should start.
  4. Unzip the zip file.

Pre-workshop Instructions

  1. Install R and RStudio For Mac users, install the necessary mandatory tools before proceeding with the installation of R packages.
  2. Install the packages required by ArchR:
if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("CNEr")
BiocManager::install("TFBSTools")
BiocManager::install("motifmatchr")
  1. Install ArchR in RStudio using the instructions here.
  2. Install the required packages in RStudio:
install.packages(c('Rcpp', 'RcppArmadillo', 'cowplot', 'Seurat', 'harmony'))
BiocManager::install("BSgenome.Hsapiens.UCSC.hg38")
install.packages('knitr', dependencies = TRUE)
require(devtools)
devtools::install_github("GreenleafLab/chromVARmotifs")
devtools::install_github("immunogenomics/presto")
  1. Restart RStudio.
  2. Open the “ArchR_demo_1_create_arrow_files.Rmd” file (download here as explained above) in RStudio.
  3. Press the Knit button.
  4. Install MACS using the instructions here. This step is not required but good to have. If you face installation issues, please skip this step, you can use the default peak caller from ArchR.
  5. If you have access to Wynton, you can alternatively follow these instructions to get ready to run the demo. Note: If you see a warning about installing from source, respond with ‘y’ for yes If your installations were successful, RStudio will run all the steps and compile an HTML document that should look like the file named “ArchR_demo_1_create_arrow_files.html” in the workshop materials. It may take some time to run through all the steps.

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