JMP Genomics is a specialized yet broad tool for analyzing genetic, genomic and other “-omic” data.
Whether it's expression analysis, GWAS, predictive modeling, or plant breeding, JMP Genomics has a tool to meet the need.
This series of blog posts deals with Cross Evaluation and Progeny Simulation for barley breeding. We start with trial data from field tests, perform BLUP, create models to predict breeding values, evaluate their effectiveness with cross validation, and ultimately choose the best model to simulate multiple generations of a breeding program using cross evaluation and progeny simulation.
The first two sets of posts in this blog series dealt with Genetic Association and Expression Analysis. Click the links to access those posts. Below is the outline for the Cross Evaluation and Progeny Simulation set, beginning with this week's post, Part 1: BLUP for Breeding Trial Data.
Series Outline
Consolidating Trial Data
- Cross Evaluation and Progeny Simulation with JMP Genomics, Part 1: BLUP for Breeding Trial Data
Model Selection
- Cross Evaluation and Progeny Simulation with JMP Genomics, Part 2: Predictive Modeling for Breeding ...
Breeding Simulation
- Cross Evaluation and Progeny Simulation with JMP Genomics, Part 3: Cross Evaluation, Selection, and ...
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