Evidence map›Paper›PMID 22912880›Full record

ArticlePloS one2012

Rapid visualisation of microarray copy number data for the detection of structural variations linked to a disease phenotype.

Ian M Carr, Christine P Diggle, Kamron Khan, Chris Inglehearn, Martin McKibbin, David T Bonthron, Alexander F Markham, Rashida Anwar, Angus Dobbie, Sergio D J Pena and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 31% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
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

11 authors at 3 institutions in 2 countries.

Ian M CarrSchool of Medicine, University of Leeds, Leeds, United Kingdom. i.m.carr@leeds.ac.uk
Christine P Diggle
Kamron Khan
Chris Inglehearn
Martin McKibbin
David T Bonthron
Alexander F Markham
Rashida Anwar
Angus Dobbie
Sergio D J Pena
Manir Ali
University of Leeds · GBSt James's University Hospital · GBUniversidade Federal de Minas Gerais · BR

Funding

Cancer Research UK 600130
6 · The paper itself

Abstract

Whilst the majority of inherited diseases have been found to be caused by single base substitutions, small insertions or deletions (<1Kb), a significant proportion of genetic variability is due to copy number variation (CNV). The possible role of CNV in monogenic and complex diseases has recently attracted considerable interest. However, until the development of whole genome, oligonucleotide micro-arrays, designed specifically to detect the presence of copy number variation, it was not easy to screen an individual for the presence of unknown deletions or duplications with sizes below the level of sensitivity of optical microscopy (3-5 Mb). Now that currently available oligonucleotide micro-arrays have in excess of a million probes, the problem of copy number analysis has moved from one of data production to that of data analysis. We have developed CNViewer, to identify copy number variation that co-segregates with a disease phenotype in small nuclear families, from genome-wide oligonucleotide micro-array data. This freely available program should constitute a useful addition to the diagnostic armamentarium of clinical geneticists.

Indexed as

DNA Copy Number VariationsSoftwareAniridiaChromosome AberrationsChromosome MappingFamily HealthFemaleGenetic Association StudiesGenetic Predisposition to DiseaseGenome, HumanHumansLoss of HeterozygosityMaleOligonucleotide Array Sequence AnalysisPedigreePhenotype

Identifiers

PMID22912880
PMCPMC3422275
OpenAlexW2082810381

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.