Evidence map›Paper›PMID 23861739›Full record

ArticlePloS one2013

Fine-scale patterns of population stratification confound rare variant association tests.

Timothy D O'Connor, Adam Kiezun, Michael Bamshad, Stephen S Rich, Joshua D Smith, Emily Turner, NHLBIGO Exome Sequencing Project, ESP Population Genetics, Statistical Analysis Working Group, Suzanne M Leal, Joshua M Akey

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Article
  2. Article
  3. Strategies for the Genomic Analysis of Admixed Populations.Annual review of biomedical data science · 2023
    Review
  4. Article
  5. Review
  6. Article
  7. Article
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  11. Article
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  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
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  20. 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

10 authors.

Timothy D O'ConnorDepartment of Genome Sciences, University of Washington, Seattle, Washington, United States of America. timothydoconnor@gmail.com
Adam Kiezun
Michael Bamshad
Stephen S Rich
Joshua D Smith
Emily Turner
NHLBIGO Exome Sequencing Project
ESP Population Genetics, Statistical Analysis Working Group
Suzanne M Leal
Joshua M Akey

Funding

Clinical and Translational Science Collaborative of ClevelandUL1TR000439 · NCATS · CASE WESTERN RESERVE UNIVERSITY · PI KONSTAN, MICHAEL W. · 2012 to 2016
$50.0M
EPIDEMIOLOGY OF DEMENTIA IN THE FRAMINGHAM STUDYR01AG008122 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI AU, RHODA, SESHADRI, SUDHA · 1989 to 2015
$14.4M
Northwest Genomics CenterRC2HL102926 · NHLBI · UNIVERSITY OF WASHINGTON · PI GREEN, PHILIP P, NICKERSON, DEBORAH A · 2009 to 2009
$11.0M
Comprehensive Sequencing and Analysis of Variation in NHLBI CohortsRC2HL102925 · NHLBI · BROAD INSTITUTE, INC. · PI ALTSHULER, DAVID, GABRIEL, STACEY · 2009 to 2009
$10.2M
ARRA - NHLBI Lung Cohorts Sequencing ProjectRC2HL102923 · NHLBI · UNIVERSITY OF WASHINGTON · PI BAMSHAD, MICHAEL JOSEPH, BARNES, KATHLEEN C · 2009 to 2009
$2.6M
WHI Sequencing Project (WHISP)RC2HL102924 · NHLBI · OHIO STATE UNIVERSITY · PI CARLSON, CHRISTOPHER S, JACKSON, REBECCA D · 2009 to 2009
$2.1M
Human Exome Sequencing in Six Well-Phenotyped NHLBI CohortsRC2HL103010 · NHLBI · UNIVERSITY OF VIRGINIA · PI RICH, STEPHEN S. · 2009 to 2009
$817k
NCATS NIH HHS UL1 TR000439NHLBI NIH HHS RC2 HL-102923NHLBI NIH HHS RC2 HL102923NHLBI NIH HHS RC2 HL-102924NHLBI NIH HHS RC2 HL102924NHLBI NIH HHS RC2 HL-102925NHLBI NIH HHS RC2 HL102925NHLBI NIH HHS RC2 HL-102926NHLBI NIH HHS RC2 HL102926NHLBI NIH HHS RC2 HL-103010NHLBI NIH HHS RC2 HL103010NIA NIH HHS R01 AG008122Wellcome Trust 090532
6 · The paper itself

Abstract

Advances in next-generation sequencing technology have enabled systematic exploration of the contribution of rare variation to Mendelian and complex diseases. Although it is well known that population stratification can generate spurious associations with common alleles, its impact on rare variant association methods remains poorly understood. Here, we performed exhaustive coalescent simulations with demographic parameters calibrated from exome sequence data to evaluate the performance of nine rare variant association methods in the presence of fine-scale population structure. We find that all methods have an inflated spurious association rate for parameter values that are consistent with levels of differentiation typical of European populations. For example, at a nominal significance level of 5%, some test statistics have a spurious association rate as high as 40%. Finally, we empirically assess the impact of population stratification in a large data set of 4,298 European American exomes. Our results have important implications for the design, analysis, and interpretation of rare variant genome-wide association studies.

Indexed as

ExomeGenetic VariationModels, GeneticAllelesGene FrequencyGenetics, PopulationGenome-Wide Association StudyHigh-Throughput Nucleotide SequencingHumansPrincipal Component AnalysisSequence Analysis, DNAWhite People

Identifiers

PMID23861739
PMCPMC3701690

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.