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. 2020 Sep 11;21:233. doi: 10.1186/s13059-020-02113-0

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© The Author(s) 2020

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 4 — Correlation between genotype and local ancestry in GTEx v8 eVariants. For all eVariants reported by the overall GTEx v8 eQTL calling pipeline, we calculated the correlation between genotypes and local ancestry using the full GTEx v8 cohort. a The majority of GTEx v8 eVariants are not confounded by local ancestry when all 838 genotyped individuals are considered. b Local ancestry explains more than 70% of the variance in genotypes for a subset of GTEx v8 eVariants. Unlike a, b considers only individuals with matched genotype and gene expression data for each tissue, which reflects the sample used to call these significant associations. eQTLs with posterior probabilities of GWAS colocalization of at least 0.5 (COLOC PP4 > 0.5) are labeled with the eGene and GWAS trait