testPosteriors: Test posterior probabilities of FR given G and E

In ipw012/RIVER: R package for RIVER (RNA-Informed Variant Effect on Regulation)

Description

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).

Usage

testPosteriors(Feat, Out, emModel)

Arguments

Feat	Genomic features (G)
Out	Binary values of outlier status (E).
emModel	Estimated parameters including beta and theta via EM and selected lambdas

Value

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.

Author(s)

Yungil Kim, [e-mail]

See Also

getFuncRvFeat and getFuncRvPosteriors

Examples

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)

ipw012/RIVER documentation built on March 8, 2020, 7:54 p.m.