Inferring Relevant Cell Types for Complex Traits by Using Single-Cell Gene Expression.

ABSTRACT: Previous studies have prioritized trait-relevant cell types by looking for an enrichment of genome-wide association study (GWAS) signal within functional regions. However, these studies are limited in cell resolution by the lack of functional annotations from difficult-to-characterize or rare cell populations. Measurement of single-cell gene expression has become a popular method for characterizing novel cell types, and yet limited work has linked single-cell RNA sequencing (RNA-seq) to phenotypes of interest. To address this deficiency, we present RolyPoly, a regression-based polygenic model that can prioritize trait-relevant cell types and genes from GWAS summary statistics and gene expression data. RolyPoly is designed to use expression data from either bulk tissue or single-cell RNA-se

SUBMITTER: Calderon D 

PROVIDER: S-EPMC5673624 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature