GEEES: inferring cell-specific gene-enhancer interactions from multi-modal single-cell data.

ABSTRACT:

Motivation

Gene-enhancer interactions are central to transcriptional regulation. Current multi-modal single-cell datasets that profile transcriptome and chromatin accessibility simultaneously in a single cell are yielding opportunities to infer gene-enhancer associations in a cell type specific manner. Computational efforts for such multi-modal single-cell datasets thus far focused on methods for identification and refinement of cell types and trajectory construction. While initial attempts for inferring gene-enhancer interactions have emerged, these have not been evaluated against benchmark datasets that materialized from bulk genomic experiments. Furthermore, existing approaches are limited to inferring gene-enhancer associations at the level of grouped cells as opposed to indivi

SUBMITTER: Chen S 

PROVIDER: S-EPMC11549018 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature