ArticleAmerican journal of human genetics2009
A generalized family-based association test for dichotomous traits.
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, 4 of them syntheses that pooled 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.
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.
Who cites it
38 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder.Nature genetics · 2024Pooled it
- Genomic risk for post-traumatic stress disorder in families densely affected with alcohol use disorders.Molecular psychiatry · 2023Pooled it
- The genetic aetiology of cannabis use initiation: a meta-analysis of genome-wide association studies and a SNP-based heritability estimation.Addiction biology · 2013Pooled it
- Population structure of Hispanics in the United States: the multi-ethnic study of atherosclerosis.PLoS genetics · 2012Pooled it
- The collaborative study on the genetics of alcoholism: Genetics.Genes, brain, and behavior · 2023Review
- Benchmarking statistical methods for analyzing parent-child dyads in genetic association studies.Genetic epidemiology · 2022Review
- Pleiotropy method reveals genetic overlap between orofacial clefts at multiple novel loci from GWAS of multi-ethnic trios.PLoS genetics · 2021Article
- A unifying framework for rare variant association testing in family-based designs, including higher criticism approaches, SKATs, and burden tests.Bioinformatics (Oxford, England) · 2021Article
- Statistically efficient association analysis of quantitative traits with haplotypes and untyped SNPs in family studies.BMC genetics · 2020Article
- A comparison of popular TDT-generalizations for family-based association analysis.Genetic epidemiology · 2019Article
- Evaluation of Gene-Based Family-Based Methods to Detect Novel Genes Associated With Familial Late Onset Alzheimer Disease.Frontiers in neuroscience · 2018Article
- Generalized disequilibrium test for association in qualitative traits incorporating imprinting effects based on extended pedigrees.BMC genetics · 2017Article
- Article
- The Rare-Variant Generalized Disequilibrium Test for Association Analysis of Nuclear and Extended Pedigrees with Application to Alzheimer Disease WGS Data.American journal of human genetics · 2017Article
- Article
- On the validity of within-nuclear-family genetic association analysis in samples of extended families.Statistical applications in genetics and molecular biology · 2015Article
- Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers.Nature genetics · 2015Article
- Efficient Bayesian mixed-model analysis increases association power in large cohorts.Nature genetics · 2015Article
- Peroxisome proliferator-activated receptors α and γ are linked with alcohol consumption in mice and withdrawal and dependence in humans.Alcoholism, clinical and experimental research · 2015Article
- Rare and common variants in extracellular matrix gene Fibrillin 2 (FBN2) are associated with macular degeneration.Human molecular genetics · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Recent advances in genotyping technology make it possible to utilize large-scale association analysis for disease-gene mapping. Powerful and robust family-based association methods are crucial for successful gene mapping. We propose a family-based association method, the generalized disequilibrium test (GDT), in which the genotype differences of all discordant relative pairs are utilized in assessing association within a family. The improvement of the GDT over existing methods is threefold: (1) information beyond first-degree relatives is incorporated efficiently, yielding substantial gains in power in comparison to existing tests; (2) the GDT statistic is implemented via a robust technique that does not rely on large sample theory, resulting in further power gains, especially at high levels of significance; and (3) covariates and weights based on family size are incorporated. Advantages of the GDT over existing methods are demonstrated by extensive computer simulations and by application to recently published large-scale genome-wide linkage data from the Type 1 Diabetes Genetics Consortium (T1DGC). In our simulations, the GDT consistently outperforms other tests for a common disease and frequently outperforms other tests for a rare disease; the power improvement is > 13% in 6 out of 8 extended pedigree scenarios. All of the six strongest associations identified by the GDT have been reported by other studies, whereas only three or four of these associations can be identified by existing methods. For the T1D association at gene UBASH3A, the GDT resulted in a genome-wide significance (p = 4.3 x 10(-6)), much stronger than the published significance (p = 10(-4)).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.