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Detection of quantitative trait loci from RNA-seq data with or without genotypes using BaseQTL

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Lin, Wei 
Starr, Colin 
White, simon R 

Abstract

Detecting genetic variants associated with traits (quantitative trait loci, QTL) requires genotyped study individuals. Here, we describe BaseQTL, a Bayesian method that exploits allele-specific expression to map molecular QTL from sequencing reads (eQTL for gene expression) even when no genotypes are available. When used with genotypes to map eQTL, BaseQTL has lower error rates and increased power compared with existing QTL mapping methods. Running without genotypes limits how many tests can be performed, but due to the proximity of QTL variants to gene bodies, the 2.8% of variants within a 100kB-window that could be tested, contained 26% of eQTL detectable with genotypes. eQTL effect estimates were invariably consistent between analyses performed with and without genotypes. Often, sequencing data may be generated in absence of genotypes on patients and controls in differential expression studies, and we identified an apparent psoriasis-specific eQTL for GSTP1 in one such dataset, providing new insights into disease-dependent gene regulation.

Description

Keywords

4202 Epidemiology, 31 Biological Sciences, 42 Health Sciences, 3105 Genetics, Genetics, Human Genome, Biotechnology, 2.1 Biological and endogenous factors, 2 Aetiology

Journal Title

Nature Computational Science

Conference Name

Journal ISSN

2662-8457
2662-8457

Volume Title

Publisher

Springer Science and Business Media LLC

Rights

All rights reserved
Sponsorship
Medical Research Council (MC_UU_00002/4)
MRC (1185)
Wellcome Trust (107881/Z/15/Z)
Medical Research Council (MR/R013926/1)
MRC (unknown)
National Institute for Health and Care Research (IS-BRC-1215-20014)
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