DIDACT models a diallel experiment, the set of inbred founders and their F1 hybrids, with a Bayesian hierarchical model. The Monte Carlo (MC) sampling is extended to decision theoretic utility functions that researchers seek to maximize or minimize. One such utility function could be the power to map a QTL in a downstream F2 intercross or back cross (BC). In this framework, signal and uncertainty can be characterized in the training diallel data, and intuitively incorporated into the experimental design step of followup experiments.
Package details 


Maintainer  
License  GPL (>= 2) 
Version  1.1.1 
Package repository  View on GitHub 
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