Genetic studies of complex human diseases rely heavily on the family-based association paradigm. However, recruiting parents or siblings can be a difficult task in practice. The author proposes two alternatives, the case-spouse and the case-offspring designs, that are to be analyzed by the mating disequilibrium test. Two assumptions are required: 1) the marker genotype frequencies at conception...

Mutual information (MI) is a robust nonparametric statistical approach for identifying associations between genotypes and gene expression levels. Using the data of Problem 1 provided for the Genetic Analysis Workshop 15, we first compared a quantitative MI (Tsalenko et al. 2006 J Bioinform Comput Biol 4:259-4) with the standard analysis of variance (ANOVA) and the nonparametric Kruskal-Wallis (...

When estimating the power of genetic association studies, the allele and genotype frequencies are often assumed to be known, and the numbers of individuals with each genotype are set equal to their expectations under Hardy-Weinberg equilibrium. In fact, both allele and genotype frequencies are unknown and thus random. It has previously been suggested that ignoring uncertainty in these parameter...

Genetic association studies are a powerful tool to detect genetic variants that predispose to human disease. Once an associated variant is identified, investigators are also interested in estimating the effect of the identified variant on disease risk. Estimates of the genetic effect based on new association findings tend to be upwardly biased due to a phenomenon known as the "winner's curse." ...

With recent advances in technology, deep sequencing data will be widely used to further the understanding of genetic influence on traits of interest. Therefore not only common variants but also rare variants need to be better used to exploit the new information provided by deep sequencing data. Recently, statistical approaches for analyzing rare variants in genetic association studies have been...

OBJECTIVE The Cochran-Armitage trend test based on the linear regression model has become a standard procedure for association testing in case-control studies. In contrast, the logistic regression model is generally used for estimating effect sizes. The aim of this paper is to propose an approach that allows for association testing and parameter estimation by means of the same statistic. METH...

Promising findings from genetic association studies are commonly presented with two distinct figures: one gives the association study results and the other indicates linkage disequilibrium (LD) between genetic markers in the region(s) of interest. Fully interpreting the results of such studies requires synthesizing the information in these figures, which is generally done in a subjective and un...

Genetic association and linkage studies can provide insights into complex disease biology, guiding the development of new diagnostic and therapeutic strategies. Over the past decade, genetic association studies have largely focused on common, easy to measure genetic variants shared between many individuals. These common variants typically have subtle functional consequence and translating the r...

Population stratification of functional gene polymorphisms is a potential confounding factor in genetic association studies. The Val66Met (rs6265) single-nucleotide polymorphism in the brain-derived neurotrophic factor gene (BDNF) exhibits one of the highest variabilities in terms of allelic distribution between populations. The present study reports the distribution of BDNF Val66Met alleles in...