GTEx cis-eQTLs Track Settings
 
GTEx High-Confidence cis-eQTLs from CAVIAR   (All Regulation tracks)

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Show interactions:  all  at least one end  both ends in window 

Track height:  pixels (range: 20 to 300, default: 200)

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Draw reverse direction interactions with dashed lines


CPP (Causal Posterior Probability):

Filter items in 'Gene Symbol' field: using

Filter by Tissue (select multiple items - help)
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Data last updated at UCSC: 2021-10-27 16:34:12

Description

This track shows genetic variants likely affecting proximal gene expression in 49 human tissues from the Genotype-Tissue Expression (GTEx) V8 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.

Display Conventions

Both the CAVIAR and DAP-G tracks show gene/variant pairs for 49 GTEx tissues. Variants are linked to the genes they interact with by a line. Variants are represented by thicker-width, single-base items. Genes are represented as thinner-width items covering the length of the gene. The direction of the chevrons on the line indicate whether the variant is upstream or downstream of the gene with the chevrons always pointing from the variant to the gene. If a variant is internal to the gene, then the variant is shown as a thicker segment than the gene. Items in the track are colored according to their tissue, with the color matching those in the GTEx Gene V8 Track.

Hovering over items in the track display will show the variant ID (often a dbSNP rsID), the target gene, tissue, and posterior probablity (Causal Posterior Probability (CPP) for CAVIAR; SNP Posterior Inclusion Probability (PIP) for DAP-G). Clicking an item will show the details of that interaction with link outs to view more details on the GTEx website.

Track configuration supports filtering by tissue, gene, or posterior probability.

Methods

Details on GTEx v8 analysis, including code, can be found in the GTEx GWAS Analysis Github.

Raw data for these analyses are available from the GTEx Portal.

CAVIAR

The CAVIAR track at UCSC was created using the CAVIAR high-confidence set, which represents the high causal variants that have a causal posterior probability (CPP) of > 0.1.

DAP-G

The DAP-G track at UCSC was created using the DAP-G 95% credible set, which represents varaints with strong eQTLs signals, which are signal clusters with signal-level posterior inclusion probability (SPIP) > 0.95.

Data Access

The raw data for this track can be accessed in multiple ways. It can be explored interactively using the Table Browser or Data Integrator. You can also access the data entries in JSON format through our JSON API.

The data in this track are organized in bigBed file format. The underlying files can be obtained from our downloads server:

Individual regions or the whole set of genome-wide annotations can be obtained using our tool bigBedToBed which can be compiled from the source code or downloaded as a precompiled binary for your system from the utilities directory linked below. For example, to extract only annotations in a given region, you could use the following command:

bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/hg38/gtex/eQtl/gtexCaviar.bb -chrom=chr16 -start=34990190 -end=36727467 stdout

Credits

Thanks to GTEx investigators, analysts, and portal team for providing this data.

References

GTEx Consortium. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science. 2020 Sep 11;369(6509):1318-1330. PMID: 32913098; PMC: PMC7737656

Lee Y, Luca F, Pique-Regi R, Wen X. Bayesian Multi-SNP Genetic Association Analysis: Control of FDR and Use of Summary Statistics. bioRxiv. 2018 May 8.

Wen X, Lee Y, Luca F, Pique-Regi R. Efficient Integrative Multi-SNP Association Analysis via Deterministic Approximation of Posteriors. Am J Hum Genet. 2016 Jun 2;98(6):1114-1129. PMID: 27236919; PMC: PMC4908152

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

GTEx Consortium. The Genotype-Tissue Expression (GTEx) project. Nat Genet. 2013 Jun;45(6):580-5. PMID: 23715323; PMC: PMC4010069

GTEx Portal Documentation