getFuncRvFeat {RIVER} | R Documentation

## Posterior probabilities of FR given G

### Description

`getFuncRvFeat` computes posterior probabilities of FR (functionality of regulatory variant) given G (genomic features) and current estimate of beta (parameters between FR and G).

### Usage

    getFuncRvFeat(Feat, logistic.model, lambda)

### Arguments

`Feat` | Genomic features (G)
`logistic.model` | Logistic regression model with current estimate of beta
`lambda` | Selected lambda

### Value

probabilities of FR given genomic features, P(FR | G)

### Author(s)

Yungil Kim, ipw012@gmail.com

### See Also

`predict`

### 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$Outlier))-1) # outlier status (E)
    costs <- c(100, 10, 1, .1, .01, 1e-3, 1e-4)
    logisticAllCV <- glmnet::cv.glmnet(Feat, Out, lambda=costs, family="binomial",
            alpha = 0, nfolds=10)
    probFuncRvFeat <- getFuncRvFeat(Feat, logistic.model=logisticAllCV$glmnet.fit,
            lambda=logisticAllCV$lambda.min)

[Package RIVER version 1.6.0 Index]