Nature GeneticsGenomicsPeer-reviewed journal article
eQTL Catalogue: a compendium of uniformly processed human gene expression and splicing QTLs
Nurlan KerimoviD, James D. HayhurstiD, Kateryna Peikova, Jonathan R. ManningiD, Peter Walter, Liis KolbergiD, Marija Samoviča, Manoj Pandian SakthiveliD, Ivan KuzminiD, Stephen J. TrevanioniD, Tony BurdettiD, Simon JuppiD, Helen ParkinsoniD, Irene PapatheodorouiD, Andrew D. YatesiD, Daniel R. ZerbinoiD, Kaur AlasooiD
- Citations
- 460
- FWCI
- 40.49
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- top 1%
Abstract
An increasing number of gene expression quantitative trait locus (eQTL) studies have made summary statistics publicly available, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and colocalisation. However, differences between these datasets, in their variants tested, allele codings, and in the transcriptional features quantified, are a barrier to their widespread use. Consequently, target genes for most GWAS signals have still not been identified. Here, we present the eQTL Catalogue (https://www.ebi.ac.uk/eqtl/), a resource which contains quality controlled, uniformly recomputed QTLs from 21 eQTL studies. We find that for matching cell types and tissues, the eQTL effect sizes are highly reproducible between studies, enabling the integrative analysis of these data. Although most cis-eQTLs were shared between most bulk tissues, the analysis of purified cell types identified a greater diversity of cell-type-specific eQTLs, a subset of which also manifested as novel disease colocalisations. Our summary statistics can be downloaded by FTP, accessed via a REST API, and visualised on the Ensembl genome browser. New datasets will continuously be added to the eQTL Catalogue, enabling the systematic interpretation of human GWAS associations across many cell types and tissues.
- organism: human
- assay: bulk RNA-seq
- research focus: fine-mapping
- research focus: GWAS / association mapping
- research focus: eQTL / molecular QTL mapping
- approach: statistical model
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