Evidence map›Paper›PMID 25922366›Full record

ReviewBriefings in functional genomics2015

The impact of human copy number variation on gene expression.

Eric R Gamazon, Barbara E Stranger

Abstract readReview
In one paragraph

Review in Briefings in functional genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
81citing papers in PubMed, 2 pooled it
–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

81 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  15. Cataloging copy number variation regions and allied diversity in goat breeds spanning pan India.Mammalian genome : official journal of the International Mammalian Genome Society · 2025
    Article
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  17. Genomic structural variation contributes to evolved changes in gene expression in high-altitude Tibetan sheep.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
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21 more citing papers are in PubMed but not listed here.

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.

Eric R Gamazon
Barbara E Stranger

Funding

Harnessing GTEx to Create Transcriptome Knowledge and Inform Disease BiologyR01MH101820 · NIMH · UNIVERSITY OF CHICAGO · PI COX, NANCY J, NICOLAE, DAN LIVIU · 2013 to 2015
$2.3M
Using the Transcriptome for SNP and Gene AnnotationR01MH090937 · NIMH · UNIVERSITY OF CHICAGO · PI COX, NANCY J, NICOLAE, DAN LIVIU · 2010 to 2012
$825k
NIMH NIH HHS R01 MH090937NIMH NIH HHS R01 MH101820
6 · The paper itself

Abstract

Recent years have witnessed a flurry of important technological and methodological developments in the discovery and analysis of copy number variations (CNVs), which are increasingly enabling the systematic evaluation of their impact on a broad range of phenotypes from molecular-level (intermediate) traits to higher-order clinical phenotypes. Like single nucleotide variants in the human genome, CNVs have been linked to complex traits in humans, including disease and drug response. These recent developments underscore the importance of incorporating complex forms of genetic variation into disease mapping studies and promise to transform our understanding of genome function and the genetic basis of disease. Here we review some of the findings that have emerged from transcriptome studies of CNVs facilitated by the rapid advances in -omics technologies and corresponding methodologies.

Indexed as

Genome, HumanGenome-Wide Association StudyDNA Copy Number VariationsHumansPhenotypeTranscriptomecopy number variationeQTLsgene expressionGWAStranscriptome

Identifiers

PMID25922366
PMCPMC4592354

What OpenQuestion holds

Textmetadata
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.