Evidence map›Paper›PMID 26335686›Full record

ArticleBMC genomics2015

Whole genome sequences are required to fully resolve the linkage disequilibrium structure of human populations.

Reuben J Pengelly, William Tapper, Jane Gibson, Marcin Knut, Rick Tearle, Andrew Collins, Sarah Ennis

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.2field-weighted citation impact, top 17% 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

9 citing papers in PubMed, 16 citations in OpenAlex.

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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

7 authors at 2 institutions in 2 countries.

Reuben J PengellyHuman Genetics & Genomic Medicine, Faculty of Medicine, University of Southampton, Duthie Building (MP 808), Tremona Road, Southampton, SO16 6YD, UK. r.j.pengelly@soton.ac.uk.
William TapperHuman Genetics & Genomic Medicine, Faculty of Medicine, University of Southampton, Duthie Building (MP 808), Tremona Road, Southampton, SO16 6YD, UK. w.j.tapper@soton.ac.uk.
Jane GibsonCentre for Biological Sciences, Faculty of Natural & Environmental Sciences, University of Southampton, Southampton, UK. j.gibson@soton.ac.uk.
Marcin KnutHuman Genetics & Genomic Medicine, Faculty of Medicine, University of Southampton, Duthie Building (MP 808), Tremona Road, Southampton, SO16 6YD, UK. m.knut@soton.ac.uk.
Rick TearleComplete Genomics, Inc., Mountain View, CA, USA. rtearle@completegenomics.com.
Andrew CollinsHuman Genetics & Genomic Medicine, Faculty of Medicine, University of Southampton, Duthie Building (MP 808), Tremona Road, Southampton, SO16 6YD, UK. a.r.collins@soton.ac.uk.
Sarah EnnisHuman Genetics & Genomic Medicine, Faculty of Medicine, University of Southampton, Duthie Building (MP 808), Tremona Road, Southampton, SO16 6YD, UK. s.ennis@soton.ac.uk.
University of Southampton · GBComplete Genomics (United States) · US

Funding

Biotechnology and Biological Sciences Research Council
6 · The paper itself

Abstract

backgroundAn understanding of linkage disequilibrium (LD) structures in the human genome underpins much of medical genetics and provides a basis for disease gene mapping and investigating biological mechanisms such as recombination and selection. Whole genome sequencing (WGS) provides the opportunity to determine LD structures at maximal resolution.

resultsWe compare LD maps constructed from WGS data with LD maps produced from the array-based HapMap dataset, for representative European and African populations. WGS provides up to 5.7-fold greater SNP density than array-based data and achieves much greater resolution of LD structure, allowing for identification of up to 2.8-fold more regions of intense recombination. The absence of ascertainment bias in variant genotyping improves the population representativeness of the WGS maps, and highlights the extent of uncaptured variation using array genotyping methodologies. The complete capture of LD patterns using WGS allows for higher genome-wide association study (GWAS) power compared to array-based GWAS, with WGS also allowing for the analysis of rare variation. The impact of marker ascertainment issues in arrays has been greatest for Sub-Saharan African populations where larger sample sizes and substantially higher marker densities are required to fully resolve the LD structure.

conclusionsWGS provides the best possible resource for LD mapping due to the maximal marker density and lack of ascertainment bias. WGS LD maps provide a rich resource for medical and population genetics studies. The increasing availability of WGS data for large populations will allow for improved research utilising LD, such as GWAS and recombination biology studies.

Indexed as

Genetics, PopulationGenome, HumanBase SequenceGene FrequencyGenetic MarkersGenotyping TechniquesHumansLinkage DisequilibriumPhysical Chromosome MappingSample SizeGenetic Markers

Identifiers

PMID26335686
PMCPMC4558963
OpenAlexW2120748058

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.