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eQTL Catalogue: a compendium of uniformly processed human gene expression and splicing QTLs

By Nurlan Kerimov, James D. Hayhurst, Kateryna Peikova, Jonathan R. Manning, Peter Walter, Liis Kolberg, Marija Samoviča, Manoj Pandian Sakthivel, Ivan Kuzmin, Stephen J. Trevanion, Tony Burdett, Simon Jupp, Helen Parkinson, Irene Papatheodorou, Andrew Yates, Daniel R. Zerbino, Kaur Alasoo

Posted 29 Jan 2020
bioRxiv DOI: 10.1101/2020.01.29.924266

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.

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