getFuncRvFeat: Posterior probabilities of FR given G

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

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, [e-mail]

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)

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