JUMP {JUMP}

Replicability Analysis of High-Throughput Experiments

Description

Replicability Analysis of High-Throughput Experiments

Usage

JUMP(pvals1, pvals2, alpha = 0.05, lambda = seq(0.01, 0.8, 0.01))

Arguments

pvals1

A numeric vector of p-values from study 1.

pvals2

A numeric vector of p-values from study 2.

alpha

The FDR level to control, default is 0.05.

lambda

The values of the tuning parameter to estimate pi_0. Must be in [0,1), default is seq(0.01, 0.8, 0.01).

Value

a list with the following elements:

p.max

The maximum of p-values across two studies.

jump.thr

The estimated threshold of p.max to control FDR at level alpha.

Examples

# Simulate p-values in two studies
m = 10000
h = sample(0:3, m, replace = TRUE, prob = c(0.9, 0.025, 0.025, 0.05))
states1 = rep(0, m); states2 = rep(0, m)
states1[which(h==2|h==3)] = 1; states2[which(h==1|h==3)] = 1
z1 = rnorm(m, states1*2, 1)
z2 = rnorm(m, states2*3, 1)
p1 = 1 - pnorm(z1); p2 = 1 - pnorm(z2)
# Run JUMP to identify replicable signals
res.jump = JUMP(p1, p2, alpha = 0.05)
sig.idx = which(res.jump$p.max <= res.jump$jump.thr)