solGS: a web-based tool for genomic selection
Genomic selection promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits
Abstract
Genomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, analysis, and sharing. A bioinformatics infrastructure for data storage and access, and user-friendly web-based tool for analysis and sharing output is needed to make GS more practical for breeders.
The authors have developed a web-based tool, called solGS, for predicting genomic estimated breeding values (GEBVs) of individuals, using a Ridge-Regression Best Linear Unbiased Predictor (RR-BLUP) model.
This work is part of the “Next Generation Cassava Breeding Project” which is supported by the UK Department for International Development, in partnership with the Bill & Melinda Gates Foundation.
Citation
Isaak Y Tecle, Jeremy D Edwards, Naama Menda, Chiedozie Egesi, Ismail Y Rabbi, Peter Kulakow, Robert Kawuki, Jean-Luc Jannink and Lukas A Mueller. solGS: a web-based tool for genomic selection. BMC Bioinformatics 2014 15:398 https://doi.org/10.1186/s12859-014-0398-7