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 2.27.1 Index]