With the availability of DNA-based molecular markers during early 1980s and that of
sophisticated statistical tools in late 1980s and later, it became possible to identify genomic …

Background Sesame is a rare example of non-model and minor crop for which numerous
genetic loci and candidate genes underlying features of interest have been disclosed at …

We present a comprehensive statistical framework to analyze data from genome-wide
association studies of polygenic traits, producing interpretable findings while controlling the …

Background Selection of an appropriate statistical significance threshold in genome-wide
association studies is critical to differentiate true positives from false positives and false …

Modern scientific studies often require the identification of a subset of explanatory variables.
Several statistical methods have been developed to automate this task, and the framework …

Discovery of genetic variants underlying bacterial phenotypes and the prediction of
phenotypes such as antibiotic resistance are fundamental tasks in bacterial genomics …

In the statistical analysis of genome-wide association data, it is challenging to precisely
localize the variants that affect complex traits, due to linkage disequilibrium, and to maximize …

Motivation Linear or nonlinear interactions of multiple single-nucleotide polymorphisms
(SNPs) play an important role in understanding the genetic basis of complex human …

All common genome-wide association (GWA) methods rely on population structure
correction, to avoid false genotype-to-phenotype associations. However, population …

High-dimensional group inference is an essential part of statistical methods for analysing
complex data sets, including hierarchical testing, tests of interaction, detection of …