IIn this workshop, we will provide a valuable introduction to the current best practices for ATAC-seq assays, high quality data generation and computational analysis workflow. Then, we will walk the participants through the analysis of an ATAC-seq data set. single cell ATAC-seq data analysis will be briefly covered at the end by comparing to the bulk ATAC-seq data analysis. Detailed tutorials including R scripts will be provided for reproducibility and follow-up exploration.
Expectation: After this workshop, participants should be able to apply the learned skills to analyzing their own ATAC-seq data, provide constructive feedback to experimenters who expect to generate high-quality ATAC-seq data, and identify ATAC-seq data of reliable quality for further analysis.
Participants are expected to have basic knowledge as follows:
Basic understanding on how ATAC-seq data are generated is helpful but not required. Please refer to the following reference for detailed information about the ATAC-seq technology.
Jason Buenrostro, Beijing Wu, Howard Chang, William Greenleaf. ATAC-seq: A Method for Assaying Chromatin Accessibility Genome-Wide. Curr Protoc Mol Biol. 2015; 109: 21.29.1–21.29.9. doi:[10.1002/0471142727.mb2129s109](https://dx.doi.org/10.1002%2F0471142727.mb2129s109).
Please refer to the following resource to preprocess the ATAC-seq data prior to performing quality assessment using the ATACseqQC package.
The Additional File 1 from our publication (Ou et al., 2018; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5831847/)
Participants are expected to have basic knowledge about R and several R packages as described above in advance. To follow along the hands-on session, we recommend participants bring your own laptop. We will post a Docker image with required packages and data pre-installed for you to download and run the analysis within a Docker container. If you will use the Docker image, please get Docker installed (https://www.docker.com/get-started) in advance. For participants who wish to install all packages by themselves, you will also need to install the following computing tools.
The following R/Bioconductor packages will be explicitly used:
|Introduction to ATAC-seq||5m|
|Preprocessing of ATAC-seq data||5m|
|ATAC-seq data QC workflow||10m|
|Downstream ATAC-seq data analysis||5m|
|Hands on session||30m|
|Q & A||5m|