| Literature DB >> 33734353 |
Gal Yankovitz1, Ofir Cohn1, Eran Bacharach1, Naama Peshes-Yaloz1, Yael Steuerman1, Fuad A Iraqi2, Irit Gat-Viks1.
Abstract
Recent computational methods have enabled the inference of the cell-type-specificity of eQTLs based on bulk transcriptomes from highly heterogeneous tissues. However, these methods are limited in their scalability to highly heterogeneous tissues and limited in their broad applicability to any cell-type specificity of eQTLs. Here we present and demonstrate Cell Lineage Genetics (CeL-Gen), a novel computational approach that allows inference of eQTLs together with the subsets of cell types in which they have an effect, from bulk transcriptome data. To obtain improved scalability and broader applicability, CeL-Gen takes as input the known cell lineage tree and relies on the observation that dynamic changes in genetic effects occur relatively infrequently during cell differentiation. CeL-Gen can therefore be used not only to tease apart genetic effects derived from different cell types but also to infer the particular differentiation steps in which genetic effects are altered.Entities:
Keywords: cell lineage; cell type; eQTL
Mesh:
Year: 2021 PMID: 33734353 PMCID: PMC8049554 DOI: 10.1093/genetics/iyab016
Source DB: PubMed Journal: Genetics ISSN: 0016-6731 Impact factor: 4.562