solGS: A Bioinformatics Solution for Genomic Selection

Genomic selection (GS) is a new breeding paradigm with a potential to increase rate of gain from selection for quantitative traits. A major challenge for breeders using GS approach is the organization, management, statistical analysis, visualization of the large-scale raw data and analysis output, and sharing data with the research community. To overcome this challenge, we are developing an open source bioinformatics solution and a web-tool called solGS. The database backend of the tool stores phenotype and genotype data, and experimental metadata. Whereas an intuitive web-interface allows you to build prediction model and apply the model to predict genomic estimated breeding values (GEBVs) of selection populations. The statistical analysis is based on rrBLUP R package and uses kinship-BLUP method to predict breeding values. The web-interface enables you to simultaneously build prediction models for multiple traits and apply selection index. The analysis output is graphically visualized on the browser and also downloadable in text format.

solGS is, currently, used by the NextGen Cassava Breeding Project (http://nextgencassava.org) and implemented on http://cassavabase.org/solgs.