Evidence map›Paper›PMID 19333967›Full record

ArticleGenetic epidemiology2009

Case-control association testing in the presence of unknown relationships.

Yoonha Choi, Ellen M Wijsman, Bruce S Weir

Abstract read
In one paragraph

Article in Genetic epidemiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.

0numbers the graph read from it
0cells of the map it votes in
63citing 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

63 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Detecting inbreeding depression in structured populations.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  7. Construction of relatedness matrices in autopolyploid populations using low-depth high-throughput sequencing data.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. To Modify or Not to Modify: Allele-Specific Effects of 3'UTR-Journal of the American Heart Association · 2022
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article

3 more citing papers are in PubMed but not listed here.

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.

Yoonha ChoiDepartment of Biostatistics, University of Washington, Seattle, 98195-7720, USA.
Ellen M Wijsman
Bruce S Weir

Funding

THERAPEUTIC EFFECTS OF INTRA-NASAL INSULIN DETEMIRP50AG005136 · NIA · UNIVERSITY OF WASHINGTON · PI JAYADEY, SUMAN · 1985 to 2019
$57.2M
PREVALENCE /INCIDENCE /RISK FACTORS FOR DEMENTIA ON GUAMP01AG014382 · NIA · UNIVERSITY OF WASHINGTON · PI PERL, DANIEL P · 1997 to 2006
$13.4M
Theoretical Population Genetics SupplementR01GM075091 · NIGMS · UNIVERSITY OF WASHINGTON · PI WEIR, BRUCE S. · 2006 to 2020
$4.7M
Genomic Analysis of Alzheimer's Disease GenesR37AG011762 · NIA · UNIVERSITY OF WASHINGTON · PI SCHELLENBERG, GERARD DAVID · 2004 to 2013
$2.7M
GENOMIC ANALYSIS OF ALZHEIMERS DISEASE GENESR01AG011762 · NIA · UNIVERSITY OF WASHINGTON · PI SCHELLENBERG, GERARD DAVID · 1994 to 2002
$689k
NIA NIH HHS AG05136NIA NIH HHS AG11762NIA NIH HHS AG14382NIA NIH HHS P01 AG014382NIA NIH HHS P50 AG005136NIA NIH HHS R01 AG011762NIA NIH HHS R37 AG011762NIGMS NIH HHS GM075091NIGMS NIH HHS R01 GM075091
6 · The paper itself

Abstract

Genome-wide association studies result in inflated false-positive results when unrecognized cryptic relatedness exists. A number of methods have been proposed for testing association between markers and disease with a correction for known pedigree-based relationships. However, in most case-control studies, relationships are generally unknown, yet the design is predicated on the assumption of at least ancestral relatedness among cases. Here, we focus on adjusting cryptic relatedness when the genealogy of the sample is unknown, particularly in the context of samples from isolated populations where cryptic relatedness may be problematic. We estimate cryptic relatedness using maximum-likelihood methods and use a corrected chi(2) test with estimated kinship coefficients for testing in the context of unknown cryptic relatedness. Estimated kinship coefficients characterize precisely the relatedness between truly related people, but are biased for unrelated pairs. The proposed test substantially reduces spurious positive results, producing a uniform null distribution of P-values. Especially with missing pedigree information, estimated kinship coefficients can still be used to correct non-independence among individuals. The corrected test was applied to real data sets from genetic isolates and created a distribution of P-value that was close to uniform. Thus, the proposed test corrects the non-uniform distribution of P-values obtained with the uncorrected test and illustrates the advantage of the approach on real data.

Indexed as

Genome-Wide Association StudyAllelesCase-Control StudiesComputational BiologyGenetic MarkersGenetics, PopulationGenome, HumanHumansLikelihood FunctionsModels, GeneticModels, StatisticalPedigreePolymorphism, Single NucleotideRiskGenetic Markers

Identifiers

PMID19333967
PMCPMC2790016

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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.