Abstract
BackgroundIt was previously reported that an association analysis based on haplotype clusters increased power over single-locus tests, and that another association test based on diplotype trend regression analysis outperformed other, more common association approaches. We suggest a novel algorithm to combine haplotype cluster- and diplotype-based analyses.MethodsDiplotyper combines a novel algorithm designed to cluster haplotypes of interest from a given set of haplotypes with two existing tools: Haploview, for analyses of linkage disequilibrium blocks and haplotypes, and PLINK, to generate all possible diplotypes from given genotypes of samples and calculate linear or logistic regression. In addition, procedures for generating all possible diplotypes from the haplotype clusters and transforming these diplotypes into PLINK formats were implemented.ResultsDiplotyper is a fully automated tool for performing association analysis based on diplotypes in a population. Diplotyper was tested through association analysis of hepatic lipase (LIPC) gene polymorphisms or diplotypes and levels of high-density lipoprotein (HDL) cholesterol.ConclusionsDiplotyper is useful for identifying more precise and distinct signals over single-locus tests.
Highlights
It was previously reported that an association analysis based on haplotype clusters increased power over single-locus tests, and that another association test based on diplotype trend regression analysis outperformed other, more common association approaches
We investigated possible associations between LIPC single nucleotide polymorphism (SNP) or diplotypes and high-density lipoprotein (HDL)-C levels in a Korean population consisting of 7,536 individuals
Many software tools like Haploview [2] and PLINK [3] provide statistical methods for haplotype association tests, most of which focus on only a singlehaplotype
Summary
It was previously reported that an association analysis based on haplotype clusters increased power over single-locus tests, and that another association test based on diplotype trend regression analysis outperformed other, more common association approaches. We suggest a novel algorithm to combine haplotype cluster- and diplotype-based analyses. Causal mutations for health conditions with genetic bases can be identified through finding associations with haplotypes, a form of correlation known as linkage disequilibrium (LD) [1]. The Haploview tool provides computation of LD and population haplotype patterns from genotype data [2]. The PLINK tool set [3] accomplishes diverse functions including a module carrying out Expectation-Maximization (EM) algorithm [4]. WHAP was developed to perform haplotype-based association analysis in population and family samples using single nucleotide polymorphism (SNP) data [5]. An additional software tool was elaborated for carrying out haplotype association analysis in unrelated individuals [6].
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