Normalization benchmark of ATAC-seq datasets shows the importance of accounting for GC-content effects.

ABSTRACT: The assay for transposase-accessible chromatin using sequencing (ATAC-seq) allows the study of epigenetic regulation of gene expression by assessing chromatin configuration for an entire genome. Despite its popularity, there have been limited studies investigating the analytical challenges related to ATAC-seq data, with most studies leveraging tools developed for bulk transcriptome sequencing. Here, we show that GC-content effects are omnipresent in ATAC-seq datasets. Since the GC-content effects are sample specific, they can bias downstream analyses such as clustering and differential accessibility analysis. We introduce a normalization method based on smooth-quantile normalization within GC-content bins and evaluate it together with 11 different normalization procedures on 8 public ATAC-

SUBMITTER: Van den Berge K 

PROVIDER: S-EPMC9701614 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature