Hierarchical annotation of eQTLs by H-eQTL enables identification of genes with cell type-divergent regulation
While context-type-specific regulation of genes is largely determined by cis-regulatory regions, attempts to identify cell type-specific eQTLs are complicated by the nested nature of cell types. We present hierarchical eQTL (H-eQTL), a network-based model for hierarchical annotation of bulk-derived eQTLs to levels of a cell type tree using single-cell chromatin accessibility data and no clustering of cells into discrete cell types. Using our model, we annotate bulk-derived eQTLs from the developing brain with high specificity to levels of a cell type hierarchy, which allows sensitive detection of genes with multiple distinct non-coding elements regulating their expression in different cell types.
Authors
- Katherine S. Pollard (ORCID: https://orcid.org/0000-0002-9870-6196)
- Pawel F. Przytycki (ORCID: https://orcid.org/0000-0002-3360-6936)
Institutions
- Boston University (US)
- Gladstone Institutes (US)
- Chan Zuckerberg Initiative (United States) (US)
Publication Details
- Journal
- Genome biology
- Published
- 2024-11-25
- DOI
- https://doi.org/10.1186/s13059-024-03440-2
- Citations
- 3
- Primary Topic
- Gene expression and cancer classification
- Type
- article
- Field-Weighted Citation Impact
- 0.70
Funders
- Additional Ventures
- National Institutes of Health
- National Institute of Mental Health