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Nature Research, Nature Computational Science, 6(1), p. 421-432, 2021

DOI: 10.1038/s43588-021-00087-y

Apollo - University of Cambridge Repository, 2021

DOI: 10.17863/cam.70615

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

This paper was not found in any repository; the policy of its publisher is unknown or unclear.
This paper was not found in any repository; the policy of its publisher is unknown or unclear.

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Data provided by SHERPA/RoMEO

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.