Now showing items 1-7 of 7
Genomic prediction of genotype x environment interaction kernel regression models
(Crop Science Society of America, 2016)
In genomic selection (GS), genotype × environment interaction (G × E) can be modeled by a marker × environment interaction (M × E). The G × E may be modeled through a linear kernel or a nonlinear (Gaussian) kernel. In this ...
Diversity analysis of 80,000 wheat accessions reveals consequences and opportunities of selection footprints
(Nature Publishing Group, 2020)
Genomic prediction in maize breeding populations with genotyping-by sequencing
(Genetics Society of America, 2013)
Genotyping-by-sequencing (GBS) technologies have proven capacity for delivering large numbers of marker genotypes with potentially less ascertainment bias than standard single nucleotide polymorphism (SNP) arrays. Therefore, ...
Chapter 11. RIndSel: selection Indices with R
RIndSel is a graphical unit interface that uses selection index theory to select individual candidates as parents for the next selection cycle. The index can be a linear combination of phenotypic values, genomic estimated ...
Chapter 10. Stochastic simulation of four linear phenotypic selection indices
Stochastic simulation can contribute to a better understanding of the problem, and has already been successfully applied to evaluate other breeding scenarios. Despite all the theories developed in this book concerning ...
isqg: a binary framework for in silico quantitative genetics
(Genetics Society of America, 2019)
The dna is the fundamental basis of genetic information, just as bits are for computers. Whenever computers are used to represent genetic data, the computational encoding must be efficient to allow the representation of ...