A Review of Bayesian Variable Selection Methods: What, How and Which Page 1 Bayesian
Analysis (2009) 4, Number 1, pp. 85–118 A Review of Bayesian Variable Selection Methods …

At least ten software packages are available for marker-based detection and localization of
loci contributing to quantitative traits in experimental animals and plants. Many of these have …

Composite interval mapping (CIM) is the most commonly used method for mapping
quantitative trait loci (QTL) with populations derived from biparental crosses. However, the …

A new statistical method for mapping quantitative trait loci (QTL), called multiple interval
mapping (MIM), is presented. It uses multiple marker intervals simultaneously to fit multiple …

Recent advances in plant genomics and molecular biology have revolutionized our
understanding of plant genetics, providing new opportunities for more efficient and …

The core of statistical inference is based on both hypothesis testing and estimation. The use
of inferential statistics for QTL identification thus includes estimation of genetic effects and …

Of many statistical methods developed to date for quantitative trait locus (QTL) analysis, only
a limited subset are available in public software allowing their exploration, comparison and …

Molecular markers have been used to map quantitative trait loci. However, they are rarely
used to evaluate effects of chromosome segments of the entire genome. The original interval …

Cross validation (CV) was used to analyze the effects of different environments and different
genotypic samples on estimates of the proportion of genotypic variance explained by QTL …

The mapping of quantitative trait loci (QTL) is to identify molecular markers or genomic loci
that influence the variation of complex traits. The problem is complicated by the facts that …