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