Evidence map›Paper›PMID 24770875›Full record

ReviewHuman genetics2014

Determining causality and consequence of expression quantitative trait loci.

A Battle, S B Montgomery

Abstract readReview
In one paragraph

Review in Human genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
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

35 citing papers in PubMed.

  1. Multi-omics Data Integration.Advances in experimental medicine and biology · 2026
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  11. Genomics in medicine: A new era in medicine.World journal of methodology · 2021
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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

2 authors.

A BattleDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA, ajbattle@cs.stanford.edu.
S B Montgomery

Funding

Clinically Relevant Genome Variation DatabaseU01HG007436 · NHGRI · STANFORD UNIVERSITY · PI BUSTAMANTE, CARLOS DANIEL, PLON, SHARON E. · 2013 to 2016
$10.5M
Methods for high-resolution analysis of genetic effects on gene expressionR01MH101814 · NIMH · UNIVERSITY OF GENEVA · PI BUSTAMANTE, CARLOS DANIEL, DERMITZAKIS, EMMANOUIL · 2013 to 2016
$2.3M
NHGRI NIH HHS U01 HG007436NIMH NIH HHS R01 MH101814
6 · The paper itself

Abstract

Expression quantitative trait loci (eQTLs) are currently the most abundant and systematically-surveyed class of functional consequence for genetic variation. Recent genetic studies of gene expression have identified thousands of eQTLs in diverse tissue types for the majority of human genes. Application of this large eQTL catalog provides an important resource for understanding the molecular basis of common genetic diseases. However, only now has both the availability of individuals with full genomes and corresponding advances in functional genomics provided the opportunity to dissect eQTLs to identify causal regulatory variants. Resolving the properties of such causal regulatory variants is improving understanding of the molecular mechanisms that influence traits and guiding the development of new genome-scale approaches to variant interpretation. In this review, we provide an overview of current computational and experimental methods for identifying causal regulatory variants and predicting their phenotypic consequences.

Indexed as

Epigenesis, GeneticGenome, HumanModels, GeneticQuantitative Trait LociComputer SimulationDatabases, GeneticGene Expression ProfilingGene Expression RegulationGenetic MarkersGenome-Wide Association StudyHumansOligonucleotide Array Sequence AnalysisPhenotypePolymorphism, Single NucleotideGenetic Markers

Identifiers

PMID24770875
PMCPMC4077614

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.