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Liu L , Chandrashekar P , Zeng B , Sanderford MD , Kumar S , Gibson G
TreeMap: a structured approach to fine mapping of eQTL variants
Bioinformatics. 2021 May 23;37(8) :1125-1134
PMID: 33135051 PMCID: PMC8150140 URL: https://www.ncbi.nlm.nih.gov/pubmed/33135051
AbstractMOTIVATION: Expression 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. RESULTS: We 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. AVAILABILITY AND IMPLEMENTATION: TreeMap is available as an R package enabled for parallel processing at https://github.com/liliulab/treemap. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Notes1367-4811 Liu, Li Orcid: 0000-0003-4002-7497 Chandrashekar, Pramod Orcid: 0000-0002-0175-0423 Zeng, Biao Sanderford, Maxwell D Kumar, Sudhir Gibson, Greg Orcid: 0000-0002-5352-5877 R01 HG008146/HG/NHGRI NIH HHS/United States Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Bioinformatics. 2021 May 23;37(8):1125-1134. doi: 10.1093/bioinformatics/btaa927.