Description Usage Arguments Value Author(s) See Also Examples
testPosteriors
computes posterior probabilities of FR (functionality
of regulatory variant) given G (genomic annotations) and E (outlier
status) with estimate of beta (parameters between FR and G) and
theta (parameters between FR and E).
1 | testPosteriors(Feat, Out, emModel)
|
Feat |
Genomic features (G) |
Out |
Binary values of outlier status (E). |
emModel |
Estimated parameters including beta and theta via EM and selected lambdas |
test posterior probabilities of FR given new outlier status (E) and genomic features (G), P(FR | G, E, beta, theta), and probable status of FR.
Yungil Kim, ipw012@gmail.com
getFuncRvFeat
and getFuncRvPosteriors
1 2 3 4 5 6 7 8 9 10 11 | dataInput <- getData(filename=system.file("extdata", "simulation_RIVER.gz",
package = "RIVER"), ZscoreThrd=1.5)
Feat <- scale(t(Biobase::exprs(dataInput))) # genomic features (G)
Out <- as.vector(as.numeric(unlist(dataInput$Outlier))-1) # outlier status (E)
theta.init <- matrix(c(.99, .01, .3, .7), nrow=2)
costs <- c(100, 10, 1, .1, .01, 1e-3, 1e-4)
logisticAllCV <- glmnet::cv.glmnet(Feat, Out, lambda=costs, family="binomial",
alpha = 0, nfolds=10)
emModelAll <- integratedEM(Feat, Out, logisticAllCV$lambda.min, logisticAllCV$glmnet.fit,
pseudoc=50, theta.init, costs, verbose=FALSE)
trainedpost <- testPosteriors(Feat, Out, emModel=emModelAll)
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