Background Genomic selection (GS) is emerging as an efficient and cost-effective method
for estimating breeding values using molecular markers distributed over the entire genome …

Many modern genomic data analyses require implementing regressions where the number
of parameters (p, eg, the number of marker effects) exceeds sample size (n). Implementing …

The detection of genotypes that predict common, complex disease is a challenge for human
geneticists. The phenomenon of epistasis, or gene‐gene interactions, is particularly …

In recent years, there has been a considerable amount of research on the use of
regularization methods for inference and prediction in quantitative genetics. Such research …

Meta-analysis is an increasingly popular tool for combining multiple different genome-wide
association studies (GWASs) in a single aggregate analysis in order to identify associations …

The mixed linear model has been widely used in genome-wide association studies (GWAS),
but its application to multi-locus GWAS analysis has not been explored and assessed. Here …

Linear mixed models (LMMs) are among the most commonly used tools for genetic
association studies. However, the standard method for estimating variance components in …

A central goal of medical genetics is to accurately predict complex disease from genotypes.
Here, we present a comprehensive analysis of simulated and real data using lasso and …

Background When designing an epigenome-wide association study (EWAS) to investigate
the relationship between DNA methylation (DNAm) and some exposure (s) or phenotype (s) …

The overfitting phenomenon happens when a statistical machine learning model learns very
well about the noise as well as the signal that is present in the training data. On the other …