Evidence map›Paper›PMID 15834813›Full record

ArticleAmerican journal of human genetics2005

Rational inferences about departures from Hardy-Weinberg equilibrium.

Jacqueline K Wittke-Thompson, Anna Pluzhnikov, Nancy J Cox

Abstract read
In one paragraph

Article in American journal of human genetics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 170 papers, 15 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
170citing papers in PubMed, 15 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

170 citing papers in PubMed, 15 syntheses or guidelines pooled it.

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  7. Meta-analysis of genetic association studies.Annals of laboratory medicine · 2015
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  14. GSTM1 and GSTT1 polymorphisms and nasopharyngeal cancer risk: an evidence-based meta-analysis.Journal of experimental & clinical cancer research : CR · 2009
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110 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.

Jacqueline K Wittke-ThompsonDepartment of Human Genetics, The University of Chicago, Chicago, IL 60637, USA.
Anna Pluzhnikov
Nancy J Cox

Funding

Whole GenomeU01GM061393 · NIGMS · UNIVERSITY OF CHICAGO · PI RATAIN, MARK J · 2000 to 2014
$39.0M
CONSORTIUM LINKAGE STUDIES OF TYPE 2 DIABETESU01DK058026 · NIDDK · UNIVERSITY OF CHICAGO · PI COX, NANCY J. · 1999 to 2004
$7.5M
Robust Methods for Indentifying Genes for Complex TraitsR01DK055889 · NIDDK · UNIVERSITY OF CHICAGO · PI COX, NANCY J. · 1998 to 2004
$1.3M
NIDDK NIH HHS DK-55889NIDDK NIH HHS DK-58026NIDDK NIH HHS R01 DK055889NIDDK NIH HHS U01 DK058026NIGMS NIH HHS U01 GM061393NIGMS NIH HHS U01-GM61393
6 · The paper itself

Abstract

Previous studies have explored the use of departure from Hardy-Weinberg equilibrium (DHW) for fine mapping Mendelian disorders and for general fine mapping. Other studies have used Hardy-Weinberg tests for genotyping quality control. To enable investigators to make rational decisions about whether DHW is due to genotyping error or to underlying biology, we developed an analytic framework and software to determine the parameter values for which DHW might be expected for common diseases. We show analytically that, for a general disease model, the difference between population and Hardy-Weinberg expected genotypic frequencies (delta) at the susceptibility locus is a function of the susceptibility-allele frequency (q), heterozygote relative risk (beta), and homozygote relative risk (gamma). For unaffected control samples, is a function of risk in nonsusceptible homozygotes (alpha), the population prevalence of disease (KP), q, beta, and gamma. We used these analytic functions to calculate and the number of cases or controls needed to detect DHW for a range of genetic models consistent with common diseases (1.1 < or = gamma < or = 10 and 0.005 < or = KP < or = 0.2). Results suggest that significant DHW can be expected in relatively small samples of patients over a range of genetic models. We also propose a goodness-of-fit test to aid investigators in determining whether a DHW observed in the context of a case-control study is consistent with a genetic disease model. We illustrate how the analytic framework and software can be used to help investigators interpret DHW in the context of association studies of common diseases.

Indexed as

AllelesGene FrequencyGenetic Predisposition to DiseaseModels, GeneticModels, StatisticalBiasCase-Control StudiesChromosome MappingGenetic MarkersGenetics, PopulationGenotypeHomozygoteHumansSoftwareGenetic Markers

Identifiers

PMID15834813
PMCPMC1196455

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.