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DIRECT-NET: An efficient method to discover cis-regulatory elements and construct regulatory networks from single-cell multiomics data

Authors :
Lihua Zhang
Jing Zhang
Qing Nie
Source :
Science advances, vol 8, iss 22
Publication Year :
2022
Publisher :
American Association for the Advancement of Science (AAAS), 2022.

Abstract

The emergence of single-cell multiomics data provides unprecedented opportunities to scrutinize the transcriptional regulatory mechanisms controlling cell identity. However, how to use those datasets to dissect the cis-regulatory element (CRE)–to–gene relationships at a single-cell level remains a major challenge. Here, we present DIRECT-NET, a machine-learning method based on gradient boosting, to identify genome-wide CREs and their relationship to target genes, either from parallel single-cell gene expression and chromatin accessibility data or from single-cell chromatin accessibility data alone. By extensively evaluating and characterizing DIRECT-NET’s predicted CREs using independent functional genomics data, we find that DIRECT-NET substantially improves the accuracy of inferring CRE-to-gene relationships in comparison to existing methods. DIRECT-NET is also capable of revealing cell subpopulation–specific and dynamic regulatory linkages. Overall, DIRECT-NET provides an efficient tool for predicting transcriptional regulation codes from single-cell multiomics data.

Details

ISSN :
23752548
Volume :
8
Database :
OpenAIRE
Journal :
Science Advances
Accession number :
edsair.doi.dedup.....cade5c0de1772e29660de49387a4a559
Full Text :
https://doi.org/10.1126/sciadv.abl7393