GS4PB

GS4PB implements a streamlined genomic prediction and selection pipeline that integrates genotyping, phenotyping, and envirotyping data for plant breeding programs.

Key Features:

• Genotypic Data Processing: Filters and imputes genotypic data.
• Data Integration: Merges genotypic and phenotypic data.
• Enviromics Collection: Collects enviromics covariates and estimates environmental kinship.
• Training Set Optimization: Optimizes training sets for genomic prediction.
• Model Cross-Validation: Cross-validates genomic prediction models.
• Multi-Trait and Multi-Environment Prediction: Implements genomic prediction for single or multiple traits across single or multiple environments.

Scientific Applications:

• Genomic Selection in Plant Breeding: Enables breeders to conduct genomic selection for advancement of breeding lines.
• Comparison of Selection Methods: Supports experiments comparing phenotypic and genomic selection approaches.
• Genetic Gain Improvement: Facilitates the use of genomics-assisted breeding methodologies to drive genetic gain in cultivar development.

Methodology:

The pipeline processes genotypic data through filtering and imputation, merges genotypic and phenotypic data, collects enviromics covariates, estimates environmental kinship, optimizes training sets, cross-validates genomic prediction models, and implements genomic prediction for single or multiple traits across single or multiple environments.