GetTopModelsPerSNPViaPosteriors: Get Top Multivariate Models
In bmass: Bayesian Multivariate Analysis of Summary Statistics

Description Usage Arguments Value Examples

Get a summary of the top models per SNP across all multivariate {U,D,I} combinations based on posterior probabilities.

1 2	GetTopModelsPerSNPViaPosteriors(DataSources, ListSNPs, ModelPriorMatrix, LogFile)

`DataSources`	A string indicating the variable names of the input datafiles and phenotypes.
`ListSNPs`	A list produced from running `bmass` containing the SNPs of interest to get marginal posteriors for.
`ModelPriorMatrix`	A matrix detailing the models being explored and their associated priors (obtained by running `GetModelPriorMatrix`)
`LogFile`	A matrix of string outputs for function logging purposes (default output from running `bmass`).

A matrix containing each model that was a SNP's top model at least once, along with related information; this matrix is appended to the input ListSNPs as a new object, TopModels (the full returned object is a list containing the input ListSNPs and the input LogFile).

Phenotypes <- c("bmass_SimulatedData1", "bmass_SimulatedData2")
bmassOutput <- bmass(Phenotypes, bmass_SimulatedSigSNPs)
bmassOutput[c("ModelPriorMatrix", "LogFile")] <- 
  GetModelPriorMatrix(Phenotypes, bmassOutput$Models,
  bmassOutput$ModelPriors, bmassOutput$LogFile)
bmassOutput[c("PreviousSNPs", "LogFile")] <-
  GetTopModelsPerSNPViaPosteriors(Phenotypes,
  bmassOutput$PreviousSNPs, bmassOutput$ModelPriorMatrix, bmassOutput$LogFile)
head(bmassOutput$PreviousSNPs$TopModels)