English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Quantitative Trait Locus (QTL) mapping in polyploids is complicated by the unobservable parental QTL configuration, especially the number of copies (dosage) of the QTL. Existing techniques estimate the parental QTL configuration using a profile likelihood approach and do not address the uncertainty in the estimates. In this paper, a Bayesian method is proposed to jointly model the parameters including the parental QTL configuration, QTL location, and QTL effects. Inference for parameters is obtained by integrating the posterior distribution of the parameters via a Markov chain Monte Carlo (MCMC) sampler, which is a hybrid of the Metropolis-Hastings, Gibbs, and reversible jump samplers. Here, because the size of the parameter space varies for different parental QTL dosages, the reversible jump is utilized in order to allow the sampler to move between parameter spaces with different dimensionalities. Additional advantage of this Bayesian technique resides in its flexibility to incorporate prior information and treat missing data augmented. As an example, our method is applied to alfalfa experimental data to identify QTL related to winter hardiness.

INTRODUCTION TO BAYESIAN QUANTITATIVE TRAIT LOCUS ANALYSIS FOR POLYPLOIDS