Background: Chromatin dysregulation is associated with developmental disorders and cancer. Numerous methods for measuring genome-wide chromatin accessibility have been developed in the genomic era to interrogate the function of chromatin regulators. A recent technique which has gained widespread use due to speed and low input requirements with native chromatin is the Assay for Transposase-Accessible Chromatin, or ATAC-seq. Biologists have since used this method to compare chromatin accessibility between two cellular conditions. However, approaches for calculating differential accessibility can yield conflicting results, and little emphasis is placed on choice of normalization method during differential ATAC-seq analysis, especially when global chromatin alterations might be expected.
Results: Using an in vivo ATAC-seq data set generated in our recent report, we observed differences in chromatin accessibility patterns depending on the data normalization method used to calculate differential accessibility. This observation was further verified on published ATAC-seq data from yeast. We propose a generalized workflow for differential accessibility analysis using ATAC-seq data. We further show this workflow identifies sites of differential chromatin accessibility that correlate with gene expression and is sensitive to differential analysis using negative controls.
Conclusions: We argue that researchers should systematically compare multiple normalization methods before continuing with differential accessibility analysis. ATAC-seq users should be aware of the interpretations of potential bias within experimental data and the assumptions of the normalization method implemented.
Keywords: ATAC-seq; Bioinformatics; Chromatin accessibility; Differential accessibility; Genomics; Normalization.