DASA: a computational pipeline for differential ATAC-Seq analysis
Year: 2019
Type: other
Abstract: ATAC-Seq (Assay for Transposase-Accessible Chromatin with high-throughput Sequencing) is a powerful method to study genome-wide chromatin accessibility. Basic computational analysis of ATAC-Seq data is similar in principle to ChIP-seq analysis: reads are aligned to the genome, and peaks in the alignment pileup indicate the location of accessible regions. Differential ATAC-Seq analysis aims at identifying chromatin accessibility differences between two conditions. This allows detection of altered chromatin modification signatures, or the effect of mutations that disrupt chromatin structure that may have profound downstream effects on gene regulation. Identification of significantly different peaks between con- ditions is a challenging problem. Peak positions must be inferred from the data, and they may not be the same across samples or even biological replicates. The most commonly used signal measure, the number of reads falling inside each peak, is affected by total library size and by the total size of the accessible regions, requiring careful normalization. DASA is a complete pipeline for differential ATAC-Seq analysis. Starting from alignment pileup and called peaks in two conditions, DASA identifies and quantifies common and unique peaks, finds peaks that are significantly different, associates differential peaks with nearby genes, and automatically generates a complete report including genome browser tracks.
Institution: University of Florida
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W2969009138