Evidence map›Paper›PMID 37721944›Full record

ArticlePLoS genetics2023

eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs.

Nurlan Kerimov, Ralf Tambets, James D Hayhurst, Ida Rahu, Peep Kolberg, Uku Raudvere, Ivan Kuzmin, Anshika Chowdhary, Andreas Vija, Hans J Teras and 13 more

Open access · goldAbstract read
In one paragraph

Article in PLoS genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 4 pooled it
7.7field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

44 citing papers in PubMed, 4 syntheses or guidelines pooled it, 50 citations in OpenAlex.

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  13. OmicsPred as a centralised resource for genetic prediction of multi-omic traits.medRxiv : the preprint server for health sciences · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

23 authors at 6 institutions in 4 countries.

Nurlan KerimovInstitute of Computer Science, University of Tartu, Tartu, Estonia.ORCID 0000-0001-7660-3148
Ralf TambetsInstitute of Computer Science, University of Tartu, Tartu, Estonia.
James D HayhurstOpen Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.
Ida RahuInstitute of Computer Science, University of Tartu, Tartu, Estonia.ORCID 0000-0001-5497-5522
Peep KolbergInstitute of Computer Science, University of Tartu, Tartu, Estonia.ORCID 0000-0001-8898-8153
Uku RaudvereInstitute of Computer Science, University of Tartu, Tartu, Estonia.ORCID 0000-0001-7243-8595
Ivan KuzminInstitute of Computer Science, University of Tartu, Tartu, Estonia.
Anshika ChowdharyInstitute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany.
Andreas VijaInstitute of Computer Science, University of Tartu, Tartu, Estonia.ORCID 0009-0007-9490-6266
Hans J TerasInstitute of Computer Science, University of Tartu, Tartu, Estonia.
Masahiro KanaiAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America.ORCID 0000-0001-5165-4408
Jacob UlirschAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Mina RytenDepartment of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom.
John HardyDepartment of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom.
Sebastian GuelfiDepartment of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom.
Daniah TrabzuniDepartment of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom.ORCID 0000-0003-4826-9570
Sarah Kim-HellmuthInstitute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany.ORCID 0000-0001-8791-5729
William RaynerInstitute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany.
Hilary FinucaneAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Hedi PetersonInstitute of Computer Science, University of Tartu, Tartu, Estonia.
Abayomi MosakuOpen Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.
Helen ParkinsonOpen Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.
Kaur AlasooInstitute of Computer Science, University of Tartu, Tartu, Estonia.ORCID 0000-0002-1761-8881
University of Tartu · EEGreat Ormond Street Hospital · GBBroad Institute · USEuropean Bioinformatics Institute · GBHelmholtz Zentrum München · DEOpen Targets · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The eQTL Catalogue is an open database of uniformly processed human molecular quantitative trait loci (QTLs). We are continuously updating the resource to further increase its utility for interpreting genetic associations with complex traits. Over the past two years, we have increased the number of uniformly processed studies from 21 to 31 and added X chromosome QTLs for 19 compatible studies. We have also implemented Leafcutter to directly identify splice-junction usage QTLs in all RNA sequencing datasets. Finally, to improve the interpretability of transcript-level QTLs, we have developed static QTL coverage plots that visualise the association between the genotype and average RNA sequencing read coverage in the region for all 1.7 million fine mapped associations. To illustrate the utility of these updates to the eQTL Catalogue, we performed colocalisation analysis between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. Although most GWAS loci colocalised both with eQTLs and transcript-level QTLs, we found that visual inspection could sometimes be used to distinguish primary splicing QTLs from those that appear to be secondary consequences of large-effect gene expression QTLs. While these visually confirmed primary splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases.

Indexed as

Multifactorial InheritanceQuantitative Trait LociBase SequenceGenome-Wide Association StudyGenotypeHumansPolymorphism, Single Nucleotide

Identifiers

PMID37721944
PMCPMC10538656
OpenAlexW4386825686

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.