ArticleGenetic epidemiology2013
GEE-based SNP set association test for continuous and discrete traits in family-based association studies.
Article in Genetic epidemiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed.
- A comparative study of statistical methods for identifying differentially expressed genes in spatial transcriptomics.bioRxiv : the preprint server for biology · 2025Article
- Article
- A novel rare variants association test for binary traits in family-based designs via copulas.Statistical methods in medical research · 2023Article
- A comprehensive gene-centric pleiotropic association analysis for 14 psychiatric disorders with GWAS summary statistics.BMC medicine · 2021Article
- Genetic association tests in family samples for multi-category phenotypes.BMC genomics · 2021Article
- Integrative eQTL-weighted hierarchical Cox models for SNP-set based time-to-event association studies.Journal of translational medicine · 2021Article
- Gene-Based Association Testing of Dichotomous Traits With Generalized Functional Linear Mixed Models Using Extended Pedigrees: Applications to Age-Related Macular Degeneration.Journal of the American Statistical Association · 2021Article
- Detection of Genetic Overlap Between Rheumatoid Arthritis and Systemic Lupus Erythematosus Using GWAS Summary Statistics.Frontiers in genetics · 2021Article
- PopCluster: an algorithm to identify genetic variants with ethnicity-dependent effects.Bioinformatics (Oxford, England) · 2019Article
- Extended methods for gene-environment-wide interaction scans in studies of admixed individuals with varying degrees of relationships.Genetic epidemiology · 2019Article
- Efficient Variant Set Mixed Model Association Tests for Continuous and Binary Traits in Large-Scale Whole-Genome Sequencing Studies.American journal of human genetics · 2019Article
- Discovery of rare variants implicated in schizophrenia using next-generation sequencing.Journal of translational genetics and genomics · 2019Article
- Detecting Rare Mutations with Heterogeneous Effects Using a Family-Based Genetic Random Field Method.Genetics · 2018Article
- Methods and results from the genome-wide association group at GAW20.BMC genetics · 2018Article
- ADAPTIVE-WEIGHT BURDEN TEST FOR ASSOCIATIONS BETWEEN QUANTITATIVE TRAITS AND GENOTYPE DATA WITH COMPLEX CORRELATIONS.The annals of applied statistics · 2018Article
- A Powerful Test for SNP Effects on Multivariate Binary Outcomes using Kernel Machine Regression.Statistics in biosciences · 2018Article
- Evaluation of Gene-Based Family-Based Methods to Detect Novel Genes Associated With Familial Late Onset Alzheimer Disease.Frontiers in neuroscience · 2018Article
- Conditional asymptotic inference for the kernel association test.Bioinformatics (Oxford, England) · 2017Article
- Rare-variant association tests in longitudinal studies, with an application to the Multi-Ethnic Study of Atherosclerosis (MESA).Genetic epidemiology · 2017Article
- Miscellanea Dependent generalized functional linear models.Biometrika · 2017Article
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5 authors.
Funding
Abstract
Family-based genetic association studies of related individuals provide opportunities to detect genetic variants that complement studies of unrelated individuals. Most statistical methods for family association studies for common variants are single marker based, which test one SNP a time. In this paper, we consider testing the effect of an SNP set, e.g., SNPs in a gene, in family studies, for both continuous and discrete traits. Specifically, we propose a generalized estimating equations (GEEs) based kernel association test, a variance component based testing method, to test for the association between a phenotype and multiple variants in an SNP set jointly using family samples. The proposed approach allows for both continuous and discrete traits, where the correlation among family members is taken into account through the use of an empirical covariance estimator. We derive the theoretical distribution of the proposed statistic under the null and develop analytical methods to calculate the P-values. We also propose an efficient resampling method for correcting for small sample size bias in family studies. The proposed method allows for easily incorporating covariates and SNP-SNP interactions. Simulation studies show that the proposed method properly controls for type I error rates under both random and ascertained sampling schemes in family studies. We demonstrate through simulation studies that our approach has superior performance for association mapping compared to the single marker based minimum P-value GEE test for an SNP-set effect over a range of scenarios. We illustrate the application of the proposed method using data from the Cleveland Family GWAS Study.
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