Evidence map›Paper›PMID 19442770›Full record

ArticleAmerican journal of human genetics2009

Genome-wide insights into the patterns and determinants of fine-scale population structure in humans.

Shameek Biswas, Laura B Scheinfeldt, Joshua M Akey

Abstract read
In one paragraph

Article in American journal of human genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
–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

38 citing papers in PubMed.

  1. Trial
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  9. Regional surnames and genetic structure in Great Britain.Transactions (Institute of British Geographers : 1965) · 2016
    Article
  10. Article
  11. Review
  12. Article
  13. Fine-scale human genetic structure in Western France.European journal of human genetics : EJHG · 2015
    Article
  14. Article
  15. Review
  16. Review
  17. Article
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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

3 authors.

Shameek BiswasDepartment of Genome Sciences, University of Washington, Seattle, WA 98195, USA.
Laura B Scheinfeldt
Joshua M Akey

Funding

INTERDISCIPLINARY TRAINING IN GENOMIC SCIENCEST32HG000035 · NHGRI · UNIVERSITY OF WASHINGTON · PI Bruce Colston Trapnell · 1995 to 2026
$24.2M
Gene expression variation in geographically diverse human populationsR01GM078105 · NIGMS · UNIVERSITY OF WASHINGTON · PI AKEY, JOSHUA MICHAEL · 2007 to 2010
$1.1M
NHGRI NIH HHS HG00035NHGRI NIH HHS T32 HG000035NIGMS NIH HHS R01 GM078105
6 · The paper itself

Abstract

Studying genomic patterns of human population structure provides important insights into human evolutionary history and the relationship among populations, and it has significant practical implications for disease-gene mapping. Here we describe a principal component (PC)-based approach to studying intracontinental population structure in humans, identify the underlying markers mediating the observed patterns of fine-scale population structure, and infer the predominating evolutionary forces shaping local population structure. We applied this methodology to a data set of 650K SNPs genotyped in 944 unrelated individuals from 52 populations and demonstrate that, although typical PC analyses focus on the top axes of variation, substantial information about population structure is contained in lower-ranked PCs. We identified 18 significant PCs, some of which distinguish individual populations. In addition to visually representing sample clusters in PC biplots, we estimated the set of all SNPs significantly correlated with each of the most informative axes of variation. These polymorphisms, unlike ancestry-informative markers (AIMs), constitute a much larger set of loci that drive genomic signatures of population structure. The genome-wide distribution of these significantly correlated markers can largely be accounted for by the stochastic effects of genetic drift, although significant clustering does occur in genomic regions that have been previously implicated as targets of recent adaptive evolution.

Indexed as

Genetics, PopulationGenome, HumanPolymorphism, Single NucleotideRacial GroupsComputer SimulationGenetic MarkersHumansPattern Recognition, AutomatedPrincipal Component AnalysisGenetic Markers

Identifiers

PMID19442770
PMCPMC2681007

What OpenQuestion holds

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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.