testPosteriors {RIVER} | R Documentation

## Test posterior probabilities of FR given G and E

### 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, ipw012@gmail.com

### 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)

[Package RIVER version 1.11.0 Index]