Major cell-types in multiomic single-nucleus datasets impact statistical modeling of links between regulatory sequences and target genes.

ABSTRACT: Epigenomic profiling, including ATACseq, is one of the main tools used to define enhancers. Because enhancers are overwhelmingly cell-type specific, inference of their activity is greatly limited in complex tissues. Multiomic assays that probe in the same nucleus both the open chromatin landscape and gene expression levels enable the study of correlations (links) between these two modalities. Current best practices to infer the regulatory effect of candidate cis-regulatory elements (cCREs) in multiomic data involve removing biases associated with GC content by generating null distributions of matched ATACseq peaks drawn from different chromosomes. This strategy has been broadly adopted by popular single-nucleus multiomic workflows such as Signac. Here, we uncovered limitations and confound

SUBMITTER: Leblanc FJA 

PROVIDER: S-EPMC9998442 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature