Evidence map›Paper›PMID 28600440›Full record

ArticleG3 (Bethesda, Md.)2017

Constraints on eQTL Fine Mapping in the Presence of Multisite Local Regulation of Gene Expression.

Biao Zeng, Luke R Lloyd-Jones, Alexander Holloway, Urko M Marigorta, Andres Metspalu, Grant W Montgomery, Tonu Esko, Kenneth L Brigham, Arshed A Quyyumi, Youssef Idaghdour and 4 more

Open access · goldAbstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
4.0field-weighted citation impact, top 6% 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

20 citing papers in PubMed, 30 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 6 institutions in 4 countries.

Biao ZengSchool of Biological Sciences and Center for Integrative Genomics, Georgia Institute of Technology, Atlanta, Georgia 30332.
Luke R Lloyd-JonesInstitute for Molecular Biosciences, University of Queensland, Brisbane, Queensland 4072, Australia.
Alexander HollowayInstitute for Molecular Biosciences, University of Queensland, Brisbane, Queensland 4072, Australia.
Urko M MarigortaSchool of Biological Sciences and Center for Integrative Genomics, Georgia Institute of Technology, Atlanta, Georgia 30332.
Andres MetspaluEstonian Genome Center, University of Tartu, 50090, Estonia.
Grant W MontgomeryInstitute for Molecular Biosciences, University of Queensland, Brisbane, Queensland 4072, Australia.
Tonu EskoEstonian Genome Center, University of Tartu, 50090, Estonia.
Kenneth L BrighamDepartment of Medicine, Emory University, Atlanta, Georgia 30329.
Arshed A QuyyumiDepartment of Medicine, Emory University, Atlanta, Georgia 30329.
Youssef IdaghdourDivision of Biology, New York University Abu Dhabi, Saadiyat Island, United Arab Emirates.
Jian YangInstitute for Molecular Biosciences, University of Queensland, Brisbane, Queensland 4072, Australia.
Peter M VisscherInstitute for Molecular Biosciences, University of Queensland, Brisbane, Queensland 4072, Australia.
Joseph E PowellInstitute for Molecular Biosciences, University of Queensland, Brisbane, Queensland 4072, Australia.
Greg GibsonSchool of Biological Sciences and Center for Integrative Genomics, Georgia Institute of Technology, Atlanta, Georgia 30332 greg.gibson@biology.gatech.edu.ORCID 0000-0002-5352-5877
University of Queensland · AUGeorgia Institute of Technology · USEmory University · USEstonian Biocentre · EENew York University Abu Dhabi · AEUniversity of Tartu · EE

Funding

Statistical Methods for X-Chromosome Genetic DataP01GM099568 · NIGMS · UNIVERSITY OF WASHINGTON · PI WEIR, BRUCE S. · 2012 to 2016
$7.3M
eQTL mega-analysis for functional assessment of multi-enhancer gene regulationR01HG008146 · NHGRI · GEORGIA INSTITUTE OF TECHNOLOGY · PI GIBSON, GREGORY C · 2016 to 2018
$2.3M
New computational, transcriptional, and genome editing approaches to the biology of inflammatory bowel diseaseR01DK119991 · NIDDK · GEORGIA INSTITUTE OF TECHNOLOGY · PI GIBSON, GREGORY C · 2018 to 2021
$692k
NHGRI NIH HHS R01 HG008146NIDDK NIH HHS R01 DK119991NIGMS NIH HHS P01 GM099568
6 · The paper itself

Abstract

Expression quantitative trait locus (eQTL) detection has emerged as an important tool for unraveling of the relationship between genetic risk factors and disease or clinical phenotypes. Most studies use single marker linear regression to discover primary signals, followed by sequential conditional modeling to detect secondary genetic variants affecting gene expression. However, this approach assumes that functional variants are sparsely distributed and that close linkage between them has little impact on estimation of their precise location and the magnitude of effects. We describe a series of simulation studies designed to evaluate the impact of linkage disequilibrium (LD) on the fine mapping of causal variants with typical eQTL effect sizes. In the presence of multisite regulation, even though between 80 and 90% of modeled eSNPs associate with normally distributed traits, up to 10% of all secondary signals could be statistical artifacts, and at least 5% but up to one-quarter of credible intervals of SNPs within

Indexed as

Gene Expression RegulationPhysical Chromosome MappingAllelesBayes TheoremComputer SimulationHumansModels, GeneticPolymorphism, Single NucleotideQuantitative Trait Locicolocalizationfine mappinggene regulationlinkage disequilibriummultivariable regression

Identifiers

PMID28600440
PMCPMC5555460
OpenAlexW2952436701

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.