ArticleAmerican journal of human genetics2000
Family-based tests of association and linkage that use unaffected sibs, covariates, and interactions.
Article in American journal of human genetics, 2000. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 3 of them syntheses that pooled it.
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Who cites it
55 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Association study and a systematic meta-analysis of the VNTR polymorphism in the 3'-UTR of dopamine transporter gene and attention-deficit hyperactivity disorder.Journal of neural transmission (Vienna, Austria : 1996) · 2019Pooled it
- Role of dopamine receptors in ADHD: a systematic meta-analysis.Molecular neurobiology · 2012Pooled it
- Candidate gene studies of ADHD: a meta-analytic review.Human genetics · 2009Pooled it
- Association between polymorphisms of IL4, IL13, IL10, STAT6 and IFNG genes, cytokines and immunoglobulin E levels with high burden of Schistosoma mansoni in children from schistosomiasis endemic areas of Cameroon.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2023Article
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- Testing gene-environment interactions in family-based association studies using trait-based ascertained samples.Statistics in medicine · 2014Article
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- GIGI: an approach to effective imputation of dense genotypes on large pedigrees.American journal of human genetics · 2013Article
- Efficient simulation of epistatic interactions in case-parent trios.Human heredity · 2013Article
- Combining genetic association study designs: a GWAS case study.Frontiers in genetics · 2013Article
- Detecting rare variants in case-parents association studies.PloS one · 2013Article
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- Human complex trait genetics: lifting the lid of the genomics toolbox - from pathways to prediction.Current genomics · 2012Article
- Examining associations between disordered eating and serotonin transporter gene polymorphisms.The International journal of eating disorders · 2012Article
- Nonparametric Covariate-Adjusted Association Tests Based on the Generalized Kendall's Tau().Journal of the American Statistical Association · 2012Article
- Combining disease models to test for gene-environment interaction in nuclear families.Biometrics · 2011Article
- Use of principal components to aggregate rare variants in case-control and family-based association studies in the presence of multiple covariates.BMC proceedings · 2011Article
- Bias due to two-stage residual-outcome regression analysis in genetic association studies.Genetic epidemiology · 2011Article
- Fine-mapping of prostate cancer aggressiveness loci on chromosome 7q22-35.The Prostate · 2011Article
- Latent class model with familial dependence to address heterogeneity in complex diseases: adapting the approach to family-based association studies.Genetic epidemiology · 2011Article
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4 authors.
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Abstract
We extend the methodology for family-based tests of association and linkage to allow for both variation in the phenotypes of subjects and incorporation of covariates into general-score tests of association. We use standard association models for a phenotype and any number of predictors. We then construct a score statistic, using likelihoods for the distribution of phenotype, given genotype. The distribution of the score is computed as a function of offspring genotypes, conditional on parental genotypes and trait values for offspring and parents. This approach provides a natural extension of the transmission/disequilibrium test to any phenotype and to multiple genes or environmental factors and allows the study of gene-gene and gene-environment interaction. When the trait varies among subjects or when covariates are included in the association model, the score statistic depends on one or more nuisance parameters. We suggest two approaches for obtaining parameter estimates: (1) choosing the estimate that minimizes the variance of the test statistic and (2) maximizing the statistic over a nuisance parameter and using a corrected P value. We apply our methods to a sample of families with attention-deficit/hyperactivity disorder and provide examples of how covariates and gene-environment and gene-gene interactions can be incorporated.
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