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 follow-up experiments.
|License||GPL (>= 2)|
|Package repository||View on GitHub|
Install the latest version of this package by entering the following in R:
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.