Work

Approximate Genome-Based Kernel Models for Large Data Sets Including Main Effects and Interactions

Year: 2020

Type: article

Abstract: The rapid development of molecular markers and sequencing technologies has made it possible to use genomic prediction (GP) and selection (GS) in animal and plant breeding. However, when the number of observations (n) is large (thousands or more), computational difficulties when handling these large genomic kernel relationship matrices (inverting and decomposing) increase exponentially. This problem increases when genomic × environment interaction and multi-trait kernels are included in the model. In this research we propose to select a low number of lines (observations) m (m

Source: Frontiers in Genetics

DOI: 10.3389/fgene.2020.567757

Authors: Jaime Cuevas, Osval A. Montesinos-López, J. W. R. Martini, Paulino Pérez-Rodríguez, Morten Lillemo, Jose Crossa

Institutions: University of Quintana Roo, Universidad de Colima, Centro Internacional de Mejoramiento de Maíz Y Trigo, Colegio de Postgraduados, Norwegian University of Life Sciences

Language: English

Topic: Genetic and phenotypic traits in livestock

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $2,716

OpenAlex ID: W3093188317

FWCI: 1.917

Cites: 37

Cited by: 20

Related to: 10