Evidence map›Paper›PMID 25505091›Full record

ArticleBioinformatics (Oxford, England)2015

JEPEG: a summary statistics based tool for gene-level joint testing of functional variants.

Donghyung Lee, Vernell S Williamson, T Bernard Bigdeli, Brien P Riley, Ayman H Fanous, Vladimir I Vladimirov, Silviu-Alin Bacanu

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Bioinformatics (Oxford, England), 2015. 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
3.7field-weighted citation impact, top 7% 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, 32 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

7 authors at 2 institutions in 1 country.

Donghyung LeeDepartment of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Center for Biomarker Research & Personalized Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA and Lieber Institute for Brain Development, Johns Hopkins University, Baltimore, MD 21205, USA.
Vernell S WilliamsonDepartment of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Center for Biomarker Research & Personalized Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA and Lieber Institute for Brain Development, Johns Hopkins University, Baltimore, MD 21205, USA.
T Bernard BigdeliDepartment of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Center for Biomarker Research & Personalized Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA and Lieber Institute for Brain Development, Johns Hopkins University, Baltimore, MD 21205, USA.
Brien P RileyDepartment of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Center for Biomarker Research & Personalized Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA and Lieber Institute for Brain Development, Johns Hopkins University, Baltimore, MD 21205, USA.
Ayman H FanousDepartment of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Center for Biomarker Research & Personalized Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA and Lieber Institute for Brain Development, Johns Hopkins University, Baltimore, MD 21205, USA.
Vladimir I VladimirovDepartment of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Center for Biomarker Research & Personalized Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA and Lieber Institute for Brain Development, Johns Hopkins University, Baltimore, MD 21205, USA Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Center for Biomarker Research & Personalized Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA and Lieber Institute for Brain Development, Johns Hopkins University, Baltimore, MD 21205, USA Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Center for Biomarker Research & Personalized Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA and Lieber Institute for Brain Development, Johns Hopkins University, Baltimore, MD 21205, USA.
Silviu-Alin BacanuDepartment of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Center for Biomarker Research & Personalized Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA and Lieber Institute for Brain Development, Johns Hopkins University, Baltimore, MD 21205, USA.
Lieber Institute for Brain Development · USVirginia Commonwealth University · US

Funding

Project 5 - Genetic architecture of alcohol use disorder using cross-trait genetic correlations and public next-generation sequencing studiesP50AA022537 · NIAAA · VIRGINIA COMMONWEALTH UNIVERSITY · PI JILL C BETTINGER · 2014 to 2026
$19.6M
Research Education in Statistical Genetics of Substance AbuseR25DA026119 · NIDA · VIRGINIA COMMONWEALTH UNIVERSITY · PI NEALE, MICHAEL CHURTON · 2008 to 2018
$3.2M
The Molecular Genetics of Recurrent Major Depression in Chinese WomenR01MH100549 · NIMH · VIRGINIA COMMONWEALTH UNIVERSITY · PI KENDLER, KENNETH SEEDMAN · 2013 to 2015
$2.0M
Using novel eQTL-based methods to find the molecular causes of alcohol dependencyR21AA022717 · NIAAA · VIRGINIA COMMONWEALTH UNIVERSITY · PI BACANU, SILVIU-ALIN · 2014 to 2015
$382k
Using genetic overlap to dissect the genetic architecture of psychiatric diseasesR21MH100560 · NIMH · VIRGINIA COMMONWEALTH UNIVERSITY · PI BACANU, SILVIU-ALIN · 2014 to 2015
$358k
NIAAA NIH HHS 1P50AA022537NIAAA NIH HHS AA022717NIAAA NIH HHS P50 AA022537NIAAA NIH HHS R21 AA022717NIDA NIH HHS R25 DA026119NIDA NIH HHS R25DA026119NIMH NIH HHS MH100560NIMH NIH HHS R01 MH100549NIMH NIH HHS R21 MH100560
6 · The paper itself

Abstract

motivationGene expression is influenced by variants commonly known as expression quantitative trait loci (eQTL). On the basis of this fact, researchers proposed to use eQTL/functional information univariately for prioritizing single nucleotide polymorphisms (SNPs) signals from genome-wide association studies (GWAS). However, most genes are influenced by multiple eQTLs which, thus, jointly affect any downstream phenotype. Therefore, when compared with the univariate prioritization approach, a joint modeling of eQTL action on phenotypes has the potential to substantially increase signal detection power. Nonetheless, a joint eQTL analysis is impeded by (i) not measuring all eQTLs in a gene and/or (ii) lack of access to individual genotypes.

resultsWe propose joint effect on phenotype of eQTL/functional SNPs associated with a gene (JEPEG), a novel software tool which uses only GWAS summary statistics to (i) impute the summary statistics at unmeasured eQTLs and (ii) test for the joint effect of all measured and imputed eQTLs in a gene. We illustrate the behavior/performance of the developed tool by analysing the GWAS meta-analysis summary statistics from the Psychiatric Genomics Consortium Stage 1 and the Genetic Consortium for Anorexia Nervosa.

conclusionsApplied analyses results suggest that JEPEG complements commonly used univariate GWAS tools by: (i) increasing signal detection power via uncovering (a) novel genes or (b) known associated genes in smaller cohorts and (ii) assisting in fine-mapping of challenging regions, e.g. major histocompatibility complex for schizophrenia. AVAILABILITY AND IMPLEMENTATION: JEPEG, its associated database of eQTL SNPs and usage examples are publicly available at http://code.google.com/p/jepeg/. CONTACT: dlee4@vcu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Gene Expression RegulationGenome-Wide Association StudyQuantitative Trait LociSoftwareAnorexia NervosaBiomarkersCohort StudiesGene Expression ProfilingGenomicsGenotypeHumansMeta-Analysis as TopicPhenotypePolymorphism, Single NucleotideBiomarkers

Identifiers

PMID25505091
PMCPMC4393522
OpenAlexW2135735996

What OpenQuestion holds

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Registered trials

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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.