GGB-correlation-snippet.R

1. p (genes) by n (slides) matrix
2. m=p keeping fdr notation

m <- p <- 1000 nreps <- 5

n <- nreps * 2 pi0 <- 0.95

m1 <- round(m * (1-pi0)) m0 <- p - m1

params <- c(2.74886, 1.36546, 4.12844) # "IPTG-a parameters" k <- 100

a.shape <- params[1] a0.shape <- params[2] scale <- params[3]

kcorrelation <- rgamma(2*m1, shape=k, rate=k) # p49 2001 NEWTON paper DEscales <- rgamma(2*m1, shape=a0.shape, rate=scale) DEscales <- DEscales * kcorrelation

kcorrelation <- rgamma(m0, shape=k, rate=k) EEscales <- rgamma(m0 , shape=a0.shape, rate=scale) EEscales <- EEscales / kcorrelation

scales <- c(rep(DEscales, each=nreps), rep(EEscales, each=2*nreps)) X <- rgamma(n* p, a.shape, rate=scales) dim(X) <- c(n,p)

X <- t(X)

1. Graphical check

pairs(log2(X)) hist(rowMeans(log2(X)), breaks=30)