Evidence map›Paper›PMID 26048416›Full record

ArticleBMC genomics2015

Recent genomic heritage in Scotland.

Carmen Amador, Jennifer Huffman, Holly Trochet, Archie Campbell, David Porteous, Generation Scotland, James F Wilson, Nick Hastie, Veronique Vitart, Caroline Hayward and 2 more

Abstract 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 33 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

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

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  16. The genetic landscape of Scotland and the Isles.Proceedings of the National Academy of Sciences of the United States of America · 2019
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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

12 authors.

Carmen AmadorMRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK. Carmen.Amador@igmm.ed.ac.uk.
Jennifer HuffmanMRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK. Jennifer.Huffman@igmm.ed.ac.uk.
Holly TrochetMRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK. HTrochet@gmail.com.
Archie CampbellMRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK. Archie.Campbell@igmm.ed.ac.uk.
David PorteousMRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK. David.Porteous@igmm.ed.ac.uk.
Generation Scotland
James F WilsonCentre for Population Health Sciences, University of Edinburgh, Edinburgh, EH8 9AG, UK. Jim.Wilson@ed.ac.uk.
Nick HastieMRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK. Nick.Hastie@igmm.ed.ac.uk.
Veronique VitartMRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK. Veronique.Vitart@igmm.ed.ac.uk.
Caroline HaywardMRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK. Caroline.Hayward@igmm.ed.ac.uk.
Pau NavarroMRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK. Pau.Navarro@ed.ac.uk.
Chris S HaleyMRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK. Chris.Haley@roslin.ed.ac.uk.

Funding

Chief Scientist Office CZD/16/6/4Medical Research Council MC_PC_U127561128Medical Research Council MC_PC_U127592696Wellcome Trust
6 · The paper itself

Abstract

backgroundThe Generation Scotland Scottish Family Health Study (GS:SFHS) includes 23,960 participants from across Scotland with records for many health-related traits and environmental covariates. Genotypes at ~700 K SNPs are currently available for 10,000 participants. The cohort was designed as a resource for genetic and health related research and the study of complex traits. In this study we developed a suite of analyses to disentangle the genomic differentiation within GS:SFHS individuals to describe and optimise the sample and methods for future analyses.

resultsWe combined the genotypic information of GS:SFHS with 1092 individuals from the 1000 Genomes project and estimated their genomic relationships. Then, we performed Principal Component Analyses of the resulting relationships to investigate the genomic origin of different groups. We characterised two groups of individuals: those with a few sparse rare markers in the genome, and those with several large rare haplotypes which might represent relatively recent exogenous ancestors. We identified some individuals with likely Italian ancestry and a group with some potential African/Asian ancestry. An analysis of homozygosity in the GS:SFHS sample revealed a very similar pattern to other European populations. We also identified an individual carrying a chromosome 1 uniparental disomy. We found evidence of local geographic stratification within the population having impact on the genomic structure.

conclusionsThese findings illuminate the history of the Scottish population and have implications for further analyses such as the study of the contributions of common and rare variants to trait heritabilities and the evaluation of genomic and phenotypic prediction of disease.

Indexed as

Quantitative Trait, HeritableAsian PeopleBlack PeopleFemaleGenome, HumanGenotypeHumansMaleModels, GeneticPhylogeographyPolymorphism, Single NucleotidePopulation DynamicsPrincipal Component AnalysisScotlandWhite People

Identifiers

PMID26048416
PMCPMC4458001

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LicenceCC BY
Read underepoch 390

Registered trials

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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.