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This track shows genetic variants likely affecting proximal gene expression in 44 human tissues from the Genotype-Tissue Expression (GTEx) V6 data release. The data items displayed are gene expression quantitative trait loci within 1MB of gene transcription start sites (cis-eQTLs), significantly associated with gene expression and in the credible set of variants for the gene at a high confidence level (95%). Each eQTL annotation includes the significance of the association, effect size on gene expression, and the probability the eQTL is a member of the 95% credible set (the set containing all causal variants for the gene locus, at 95% confidence level).
The eQTL item color indicates the effect size attributed to the eQTL:
|light red||moderate positive|
|light blue||moderate negative|
|mixed||positive and negative effect in combined eQTL|
Gene/variant pairs occurring in multiple tissues are combined into a single item in the display. The item label shows the number of tissues where the eQTL was identified, or the tissue name and the GTEx-convention tissue color if the eQTL was identified solely in one tissue. Mouseover lists all tissues affected and the effect size. The item color reflects the largest effect size in any tissue.
Track configuration supports filtering by gene, effect size, or probability. Tissues can be selected via checkboxes or from the UCSC GTEx Body Map graphic. GTEx Combined eQTL Track Settings: hg19.
This track is a composite track containing 44 subtracks representing the GTEx eQTL tissues. Each subtrack contains all GTEx/CAVIAR eQTLs identified for that tissue. GTEx 44 Tissues eQTL Track Settings: hg19.
Laboratory and RNA-seq analysis methods for GTEx V6 are summarized in the GTEx Gene Track description page.
Cis-eQTL's were identified from GTEx RNA-seq and genotype data (variants with minor allele frequency >= 1%) in 44 tissues (those with sample size >=70) using the FastQTL mapper at 5% FDR threshold, by the GTEx Laboratory, Data Analysis and Coordinating Center (LDACC), as part of the GTEx project v6p analysis. These cis-eQTL's were then analyzed together with genome variation information (LD) using the CAVIAR statistical framework to quantify the probability a variant is causal, at the Eskin lab at UCLA, as part of GTEx downstream analysis. The UCSC track was created using the CAVIAR 95% credible set, with significance p-values and effect sizes from the LDACC analysis.
Raw data for these analyses are available from dbGaP (phs000424.v6.p1).
GTEx Consortium., Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group., Statistical Methods groups—Analysis Working Group., Enhancing GTEx (eGTEx) groups., NIH Common Fund., NIH/NCI., NIH/NHGRI., NIH/NIMH., NIH/NIDA., Biospecimen Collection Source Site—NDRI. et al. Genetic effects on gene expression across human tissues. Nature. 2017 Oct 11;550(7675):204-213. PMID: 29022597
Ongen H, Buil A, Brown AA, Dermitzakis ET, Delaneau O. Fast and efficient QTL mapper for thousands of molecular phenotypes. Bioinformatics. 2016 May 15;32(10):1479-85. PMID: 26708335; PMC: PMC4866519
Hormozdiari F, Kostem E, Kang EY, Pasaniuc B, Eskin E. Identifying causal variants at loci with multiple signals of association. Genetics. 2014 Oct;198(2):497-508. PMID: 25104515; PMC: PMC4196608