Inference of gene-environment interaction from heterogeneous case-parent trios.

In genetic epidemiology, log-linear models of population risk may be used to study the effect of genotypes and exposures on the relative risk of a disease. Such models may also include gene-environment interaction terms that allow the genotypes to modify the effect of the exposure, or equivalently, the exposure to modify the effect of genotypes on the relative risk. When a measured test locus is in linkage disequilibrium with an unmeasured causal locus, exposure-related genetic structure in the population can lead to spurious gene-environment interaction; that is, to apparent gene-environment interaction at the test locus in the absence of true gene-environment interaction at the causal locus.

Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes.

Introduction: Increasingly, logistic regression methods for genetic association studies of binary phenotypes must be able to accommodate data sparsity, which arises from unbalanced case-control ratios and/or rare genetic variants. Sparseness leads to maximum likelihood estimators (MLEs) of log-OR parameters that are biased away from their null value of zero and tests with inflated type 1 errors. Different penalized-likelihood methods have been developed to mitigate sparse-data bias.

Re-analysis of a Genome-Wide Gene-By-Environment Interaction Study of Case Parent Trios, Adjusted for Population Stratification.

We investigate the impact of confounding on the results of a genome-wide association analysis by Beaty et al., which identified multiple single nucleotide polymorphisms that appeared to modify the effect of maternal smoking, alcohol consumption, or multivitamin supplementation on risk of cleft palate. The study sample of case-parent trios was primarily of European and East Asian ancestry, and the distribution of all three exposures differed by ancestral group.

The Contribution Plot: Decomposition and Graphical Display of the RV Coefficient, with Application to Genetic and Brain Imaging Biomarkers of Alzheimer's Disease.

Background/aims: Alzheimer's disease (AD) is a chronic neurodegenerative disease that causes memory loss and a decline in cognitive abilities. AD is the sixth leading cause of death in the USA, affecting an estimated 5 million Americans. To assess the association between multiple genetic variants and multiple measurements of structural changes in the brain, a recent study of AD used a multivariate measure of linear dependence, the RV coefficient.

Sampletrees and Rsampletrees: sampling gene genealogies conditional on SNP genotype data.

Unlabelled: : The program sampletrees is a Markov chain Monte Carlo sampler of gene genealogies conditional on either phased or unphased SNP genotype data. The companion program Rsampletrees is for pre- and post-processing of sampletrees files, including setting up the files for sampletrees and storing and plotting the output of a sampletrees run.

Availability And Implementation: sampletrees is implemented in C ++.