ArticleBriefings in bioinformatics2016
Comparison of haplotype-based statistical tests for disease association with rare and common variants.
Article in Briefings in bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Breast cancer: taxonomy, distribution analysis, risk factors, predictive biomarkers, and modern treatment method.Apoptosis : an international journal on programmed cell death · 2026Review
- Bayesian LASSO for population stratification correction in rare haplotype association studies.Statistical applications in genetics and molecular biology · 2024Article
- Haplotype based testing for a better understanding of the selective architecture.BMC bioinformatics · 2023Article
- Bivariate quantitative Bayesian LASSO for detecting association of rare haplotypes with two correlated continuous phenotypes.Frontiers in genetics · 2023Article
- Genome-wide haplotype association study in imaging genetics using whole-brain sulcal openings of 16,304 UK Biobank subjects.European journal of human genetics : EJHG · 2021Article
- Reconstruction of Microbial Haplotypes by Integration of Statistical and Physical Linkage in Scaffolding.Molecular biology and evolution · 2021Article
- Comparison of haplotype-based tests for detecting gene-environment interactions with rare variants.Briefings in bioinformatics · 2020Review
- Bivariate logistic Bayesian LASSO for detecting rare haplotype association with two correlated phenotypes.Genetic epidemiology · 2019Article
- Deciphering the Emerging Complexities of Molecular Mechanisms at GWAS Loci.American journal of human genetics · 2018Review
- A Family-Based Rare Haplotype Association Method for Quantitative Traits.Human heredity · 2018Article
- Logistic Bayesian LASSO for genetic association analysis of data from complex sampling designs.Journal of human genetics · 2017Article
- Detecting rare and common haplotype-environment interaction under uncertainty of gene-environment independence assumption.Biometrics · 2017Article
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2 authors.
Funding
Abstract
Recent literature has highlighted the advantages of haplotype association methods for detecting rare variants associated with common diseases. As several new haplotype association methods have been proposed in the past few years, a comparison of new and standard methods is important and timely for guidance to the practitioners. We consider nine methods-Haplo.score, Haplo.glm, Hapassoc, Bayesian hierarchical Generalized Linear Model (BhGLM), Logistic Bayesian LASSO (LBL), regularized GLM (rGLM), Haplotype Kernel Association Test, wei-SIMc-matching and Weighted Haplotype and Imputation-based Tests. These can be divided into two types-individual haplotype-specific tests and global tests depending on whether there is just one overall test for a haplotype region (global) or there is an individual test for each haplotype in the region. Haplo.score is the only method that tests for both; Haplo.glm, Hapassoc, BhGLM and LBL are individual haplotype-specific, while the rest are global tests. For comparison, we also apply a popular collapsing method-Sequence Kernel Association Test (SKAT) and its two variants-SKAT-O (Optimal) and SKAT-C (Combined). We carry out an extensive comparison on our simulated data sets as well as on the Genetic Analysis Workshop (GAW) 18 simulated data. Further, we apply the methods to GAW18 real hypertension data and Dallas Heart Study sequence data. We find that LBL, Haplo.score (global test) and rGLM perform well over the scenarios considered here. Also, haplotype methods are more powerful (albeit more computationally intensive) than SKAT and its variants in scenarios where multiple causal variants act interactively to produce haplotype effects.
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Registered trials
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