Abstract
BackgroundIt has been repeatedly stressed that family-based samples suffer less from genetic heterogeneity and that association analyses with family-based samples are expected to be powerful for detecting susceptibility loci for rare disease. Various approaches for rare-variant analysis with family-based samples have been proposed.MethodsIn this report, performances of the existing methods were compared with the simulated data set provided as part of Genetic Analysis Workshop 19 (GAW19). We considered the rare variant transmission disequilibrium test (RV-TDT), generalized estimating equations-based kernel association (GEE-KM) test, an extended combined multivariate and collapsing test for pedigree data (known as Pedigree Combined Multivariate and Collapsing [PedCMC]), gene-level kernel and burden association tests with disease status for pedigree data (PedGene), and the family-based rare variant association test (FARVAT).ResultsThe results show that PedGene and FARVAT are usually the most efficient, and the optimal test statistic provided by FARVAT is robust under different disease models. Furthermore, FARVAT was implemented with C++, which is more computationally faster than other methods.ConclusionsConsidering both statistical and computational efficiency, we conclude that FARVAT is a good choice for rare-variant analysis with extended families.
Highlights
It has been repeatedly stressed that family-based samples suffer less from genetic heterogeneity and that association analyses with family-based samples are expected to be powerful for detecting susceptibility loci for rare disease
We considered 5 different methods for dichotomous phenotypes: the rare variant transmission disequilibrium test (RV-TDT) [11], generalized estimating equations based kernel association (GEE-KM) test [9], an extended combined multivariate and collapsing test for pedigree data (Pedigree Combined Multivariate and Collapsing [PedCMC]) [10], gene-level kernel and burden association tests with disease status for pedigree data (PedGene) [8], and the family-based rare variant association test (FARVAT) [12]
Rare variant transmission disequilibrium test RV-TDT [11] is an extension of the transmission disequilibrium test (TDT) to analyze parent–child trio data for rare-variant associations, which can adequately control for population admixture
Summary
It has been repeatedly stressed that family-based samples suffer less from genetic heterogeneity and that association analyses with family-based samples are expected to be powerful for detecting susceptibility loci for rare disease. The collapsed rare allele counts or variance inflations for multiple rare variants in a gene can be compared between affected and unaffected individuals, and several burden and variance component methods. In spite of these successful findings, the analysis with population-based samples suffers from genetic heterogeneity. Individuals in a family are genetically more homogeneous, and affected family members have an increased chance to share the same causal variants.
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