Evidence map›Paper›PMID 18697816›Full record

ArticleNucleic acids research2008

Analysis of copy number variation using quantitative interspecies competitive PCR.

Nigel M Williams, Hywel Williams, Elisa Majounie, Nadine Norton, Beate Glaser, Huw R Morris, Michael J Owen, Michael C O'Donovan

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Nucleic acids research, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 27% 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

2 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. 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

8 authors at 2 institutions in 1 country.

Nigel M WilliamsDepartment of Psychological Medicine, Wales School of Medicine, Cardiff University, Heath Park, Cardiff CF14 4XN, UK. williamsnm@cf.ac.uk
Hywel Williams
Elisa Majounie
Nadine Norton
Beate Glaser
Huw R Morris
Michael J Owen
Michael C O'Donovan
Cardiff University · GBUniversity of Wales · GB

Funding

Medical Research Council G9810900Wellcome Trust
6 · The paper itself

Abstract

Over recent years small submicroscopic DNA copy-number variants (CNVs) have been highlighted as an important source of variation in the human genome, human phenotypic diversity and disease susceptibility. Consequently, there is a pressing need for the development of methods that allow the efficient, accurate and cheap measurement of genomic copy number polymorphisms in clinical cohorts. We have developed a simple competitive PCR based method to determine DNA copy number which uses the entire genome of a single chimpanzee as a competitor thus eliminating the requirement for competitive sequences to be synthesized for each assay. This results in the requirement for only a single reference sample for all assays and dramatically increases the potential for large numbers of loci to be analysed in multiplex. In this study we establish proof of concept by accurately detecting previously characterized mutations at the PARK2 locus and then demonstrating the potential of quantitative interspecies competitive PCR (qicPCR) to accurately genotype CNVs in association studies by analysing chromosome 22q11 deletions in a sample of previously characterized patients and normal controls.

Indexed as

Genetic VariationAnimalsChromosome DeletionChromosomes, Human, Pair 22Gene DosageHumansMutationPan troglodytesPolymerase Chain ReactionPolymorphism, GeneticReference StandardsReproducibility of ResultsSequence Analysis, DNAUbiquitin-Protein Ligasesparkin proteinUbiquitin-Protein Ligases

Identifiers

PMID18697816
PMCPMC2553599
OpenAlexW2080843414

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.