Ontology highlight
ABSTRACT:
SUBMITTER: Gentzbittel L
PROVIDER: S-EPMC6537182 | biostudies-literature | 2019 May
REPOSITORIES: biostudies-literature
Gentzbittel Laurent L Ben Cécile C Mazurier Mélanie M Shin Min-Gyoung MG Lorenz Todd T Rickauer Martina M Marjoram Paul P Nuzhdin Sergey V SV Tatarinova Tatiana V TV
Genome biology 20190528 1
The explosive growth of genomic data provides an opportunity to make increased use of sequence variations for phenotype prediction. We have developed a prediction machine for quantitative phenotypes (WhoGEM) that overcomes some of the bottlenecks limiting the current methods. We demonstrated its performance by predicting quantitative disease resistance and quantitative functional traits in the wild model plant species, Medicago truncatula, using geographical locations as covariates for admixture ...[more]