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Leveraging supervised learning for functionally informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs
- Source :
- Nature Communications, Vol 12, Iss 1, Pp 1-11 (2021)
- Publication Year :
- 2021
- Publisher :
- Nature Portfolio, 2021.
-
Abstract
- Finding causal variants and genes from GWAS loci results remains a challenge. Here, the authors train a model to predict if a variant affects nearby gene expression, and apply the method to identify new possible causal eQTLs and mechanisms of GWAS loci.
- Subjects :
- Science
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 12
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Nature Communications
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.f492bfb02a464d72ae49db0b2d0594f8
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41467-021-23134-8