SSPA (version 2.12.0)

simdat: Generate simulated microarray data using the bitriangular distribution.

Description

Simulated microarray data.

Usage

simdat(mu, m, pi0, J, nullX = function(x) rnorm(x, 0, 1), nullY = function(x) rnorm(x, 0, 1), noise = 0.01)

Arguments

mu

vector of effect sizes drawn from the bitriangular distribution.

m

number of features (genes, tags, ...).

pi0

proportion of nondifferentially expressed features.

J

number of samples per group.

nullX

the distribution of nondifferentially expressed features.

nullY

the distribution of nondifferentially expressed features.

noise

standard deviation of the additive noise.

Value

Matrix of size m x (2J), containing the simulated values.

Details

details follow

Examples

##generate two-group microarray data
m <- 5000 ##number of genes
J <- 10 ##sample size per group
pi0 <- 0.8 ##proportion of non-differentially expressed genes
m0 <- as.integer(m*pi0)
mu <- rbitri(m - m0, a = log2(1.2), b = log2(4), m = log2(2)) #effect size distribution
data <- simdat(mu, m=m, pi0=pi0, J=J, noise=0.01)