Genome-Wide association studies (GWAS), based on testing one single nucleotide
polymorphism (SNP) at a time, have revolutionized our understanding of the genetics of …

Many genetic studies contain rich information on longitudinal phenotypes that require
powerful analytical tools for optimal analysis. Genetic analysis of longitudinal data that …

Motivation: Despite the widespread popularity of genome-wide association studies (GWAS)
for genetic mapping of complex traits, most existing GWAS methodologies are still limited to …

Group variable selection is an important issue in high-dimensional data modeling and most
of existing methods consider only the linear model. Therefore, a new method based on the …

Modern medicine is undergoing a paradigm shift from a" one-size-fits-all" strategy to a more
precise patient-customized therapy and medication plan. While the success of precision …

Twin studies have been adopted for decades to disentangle the relative genetic and
environmental contributions for a wide range of traits. However, heritability estimation based …

Data irregularity in cancer genomics studies has been widely observed in the form of outliers
and heavy-tailed distributions in the complex traits. In the past decade, robust variable …

Varying coefficient models are popular tools in estimating nonlinear regression functions in
functional data models. Their Bayesian variants have received limited attention in large data …

To accurately explore the interaction mechanism between Escherichia coli and
Staphylococcus aureus, we designed an ecological experiment to monoculture and co …

In high-throughput genetics studies, an important aim is to identify gene–environment
interactions associated with the clinical outcomes. Recently, multiple marginal penalization …