pauc_out: pauc_out.
In ntyet/sfdr: False Discovery Rate Estimation in Two Independent Experiments

Description Usage Arguments Value Examples

This function is to calculate false discovery proportion, partial area under ROC curve, number of true positive when we know the true status of each gene

1	pauc_out(q, lab)

`q`	a vector of p-values
`lab`	a vector of factor consistings of 0 or 1, indicating if the feater are true null or false null.

a vector of S, V, R, FDR, pauc

set.seed(1)
EE <- 1000
DE <- 100
p1 <- runif(EE)
p2 <- rbeta(DE, shape1 = .5, shape2 = 1)
p <- c(p1, p2)
lab <- as.factor(as.character(c(rep(0, EE), rep(1, DE))))
pauc_out(p, lab)