scATAC-seq Analysis Using R

Data Science Training Program

Ayushi Agrawal

Michela Traglia

Reuben Thomas

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, marker peak identification, 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.

Attendance at all three sessions is highly recommended. The subsequent sessions build upon the previous ones.

Requirements

• 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)

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.

Visit the workshop site for more details and materials.