Intrinsic bias estimation for improved analysis of bulk and single-cell chromatin accessibility profiles using SELMA.

ABSTRACT: Genome-wide profiling of chromatin accessibility by DNase-seq or ATAC-seq has been widely used to identify regulatory DNA elements and transcription factor binding sites. However, enzymatic DNA cleavage exhibits intrinsic sequence biases that confound chromatin accessibility profiling data analysis. Existing computational tools are limited in their ability to account for such intrinsic biases and not designed for analyzing single-cell data. Here, we present Simplex Encoded Linear Model for Accessible Chromatin (SELMA), a computational method for systematic estimation of intrinsic cleavage biases from genomic chromatin accessibility profiling data. We demonstrate that SELMA yields accurate and robust bias estimation from both bulk and single-cell DNase-seq and ATAC-seq data. SELMA can utili

SUBMITTER: Hu SS 

PROVIDER: S-EPMC9492688 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature