bayesGO: bayesGO function

In dongjunchung/bayesGO: bayesGO (Bayesian modeling of Gene Ontology fingerprint)

Description

Fit the bayesGO model

Usage

bayesGO(pmat, nRow = NA, nCol = NA, Vmax = NA, Kmax = NA,
  nBurnin = 20000, nMain = 10000, thin = 10, seed = 12345)

Arguments

pmat	A matrix of hypergeometric p-values
nRow	Number of rows to analyze (default: use all rows)
nCol	Number of columns to analyze (default: use all columns)
Vmax	Maximum number of row clusters (default: 0.1 * nRow)
Kmax	Maximum number of column clusters (default: 0.1 * nCol)
nBurnin	MCMC: Number of burn-in iterations (default: 20000)
nMain	MCMC: Number of main iterations (default: 10000)
thin	Thinning (default: 10)
seed	Random seed (default: 12345)

Examples

data(simul)
fit.bayesGO <- bayesGO( simul, nBurnin=10, nMain=10, thin=1 )
fit.bayesGO
predict( fit.bayesGO, thresGene=0.9, thresTerm=0.9 )
plot( fit.bayesGO, thresGene=0.9, thresTerm=0.9 )

dongjunchung/bayesGO documentation built on March 1, 2020, 3:44 a.m.