Evidence map›Paper›PMID 17597776›Full record

ReviewNature genetics2007

Methods and strategies for analyzing copy number variation using DNA microarrays.

Nigel P Carter

Abstract readReview
In one paragraph

Review in Nature genetics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 220 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
220citing papers in PubMed, 3 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

220 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  15. Copy number variations at theFrontiers in plant science · 2024
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160 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

1 author.

Nigel P CarterWellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK. npc@sanger.ac.uk

Funding

Wellcome Trust 077008
6 · The paper itself

Abstract

The association of DNA copy-number variation (CNV) with specific gene function and human disease has been long known, but the wide scope and prevalence of this form of variation has only recently been fully appreciated. The latest studies using microarray technology have demonstrated that as much as 12% of the human genome and thousands of genes are variable in copy number, and this diversity is likely to be responsible for a significant proportion of normal phenotypic variation. Current challenges involve developing methods not only for detecting and cataloging CNVs in human populations at increasingly higher resolution but also for determining the association of CNVs with biological function, recent human evolution, and common and complex human disease.

Indexed as

Gene DosageGenetic VariationChromosomes, Artificial, BacterialChromosomes, Human, Pair 18Cloning, MolecularDNA, ComplementaryGenome, HumanGenotypeHumansNucleic Acid HybridizationOligonucleotide Array Sequence AnalysisPhenotypePolymerase Chain ReactionPolymorphism, Single NucleotideDNA, Complementary

Identifiers

PMID17597776
PMCPMC2697494

What OpenQuestion holds

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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.