simdat {SSPA}R Documentation

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.

Details

details follow

Value

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

Author(s)

Maarten van Iterson

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)

[Package SSPA version 2.22.1 Index]