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bioRxiv · 10.1101/2020.05.31.125880

TreeMap: A Structured Approach to Fine Mapping of eQTL Variants

Liu, L.·Chandrashekar, P.·Zeng, B.·Sanderford, M. D.·Kumar, S.·Gibson, G.
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Abstract

MotivationExpression quantitative trait loci (eQTL) harbor genetic variants modulating gene transcription. Fine mapping of regulatory variants at these loci is a daunting task due to the juxtaposition of causal and linked variants at a locus as well as the likelihood of interactions among multiple variants. This problem is exacerbated in genes with multiple cis-acting eQTL, where superimposed effects of adjacent loci further distort the association signals. ResultsWe developed a novel algorithm, TreeMap, that identifies putative causal variants in cis-eQTL accounting for multisite effects and genetic linkage at a locus. Guided by the hierarchical structure of linkage disequilibrium, TreeMap performs an organized search for individual and multiple causal variants. Via extensive simulations, we show that TreeMap detects co-regulating variants more accurately than current methods. Furthermore, its high computational efficiency enables genome-wide analysis of long-range eQTL. We applied TreeMap to GTEx data of brain hippocampus samples and transverse colon samples to search for eQTL in gene bodies and in 4 Mbps gene-flanking regions, discovering numerous distal eQTL. Furthermore, we found concordant distal eQTL that were present in both brain and colon samples, implying long-range regulation of gene expression. AvailabilityTreeMap is available as an R package enabled for parallel processing at https://github.com/liliulab/treemap.

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Liu, L., Chandrashekar, P., Zeng, B., Sanderford, M. D., Kumar, S., Gibson, G.. 2020-05-31. TreeMap: A Structured Approach to Fine Mapping of eQTL Variants. https://doi.org/10.1101/2020.05.31.125880

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