Hands-on ATAC-Seq Data Analysis for Identification of Chromatin Accessibility Using Linux & R

Map open chromatin with ATAC-Seq, in Linux and R

ATAC-Seq shows you which parts of the genome are accessible — where the regulatory machinery can physically reach the DNA. It needs very little input material and a short protocol, which is why it has become the standard method for profiling the regulatory landscape of a cell type or condition. This course covers the full analysis in Linux and R.

What you work through

• ATAC-Seq in depth — how Tn5 transposase tagging works, what accessibility does and does not tell you, and how ATAC-Seq relates to ChIP-Seq and DNase-Seq.
• Quality control — the three metrics that decide whether a library is usable: TSS enrichment, fragment-size periodicity and FRiP.
• Alignment and filtering — removing mitochondrial reads, duplicates and blacklist regions, each of which will distort your results if left in.
• Peak calling — identifying accessible regions and building a consensus set across replicates.
• Differential accessibility — finding regions that open or close between conditions.
• Motif and footprinting analysis — working out which transcription factors are driving the changes you found.
• Annotation — linking accessible regions to promoters, enhancers and nearby genes.

The quality control is not optional here

ATAC-Seq is unusually unforgiving. Slightly too much enzyme cuts through nucleosomal DNA and destroys the signal; degraded nuclei produce a library that sequences perfectly and means nothing. Both failures are invisible unless you look at the fragment-size distribution and TSS enrichment — so the course teaches you to read those before analysing anything. Our guide to ATAC-Seq quality control covers the same ground in writing.

What you can do afterwards

Take raw ATAC-Seq data through QC, alignment, filtering, peak calling, differential accessibility and motif analysis — and recognise a failed experiment before you spend a week analysing it.

We also run this analysis directly as an ATAC-Seq analysis service.

Who it suits

Researchers studying gene regulation, chromatin or development who have ATAC-Seq data, and bioinformaticians adding epigenomics to an existing RNA-Seq skill set. Linux and R are taught as part of the course.