by Daniel Runcie, Sayan Mukhergee
Reference: Runcie, D., & Mukherjee, S. (2013). Dissecting High-Dimensional Phenotypes with Bayesian Sparse Factor Analysis of Genetic Covariance Matrices. Genetics, 194(3), 753–767. http://doi.org/10.1534/genetics.113.151217
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Published version in MATLAB on website:
- includes Ayroles_et_al_Competitive_fitness, Simulations with half-sib design
- should be able to replicate all analyses from paper (up to Monte-carlo error in Gibbs and in simulations)
- Fixed calculation of genetic and interaction specific effects. The calculation and corresponding text of the paper missed
$A^{-1}$ . This should not greatly affect the results of the analyses presented in the paper, but will need to check. It doesn't affect Ayroles analysis.
Nearly complete re-write of the model code, but should maintain identical function (I believe)
- variables have been re-named to more closely correspond to the paper
- sampler function has been re-written to only sample.
- A new function initializes the sampler, only run once
- sampler function starts where the previous run left off (including maintaining the random number generator), so should be the same as running one continuous chain
R clone of V2.0 Matlab code
- Functionality should be identical. Worth checking. Note that the RNG is different.
- embeded in the Gibbs sampler are two versions of each sampler function, a native R version, and a Rcpp version. They should be identical (up to RNG differences). The Rcpp function has the same name and arguments, but with "_c" appended to the function name.