makeExampleDESeqDataSet_multifac {pcaExplorer} | R Documentation

## Make a simulated DESeqDataSet for two or more experimental factors

### Description

Constructs a simulated dataset of Negative Binomial data from different conditions. The fold changes between the conditions can be adjusted with the `betaSD_condition` and the `betaSD_tissue` arguments.

### Usage

    makeExampleDESeqDataSet_multifac(n = 1000, m = 12,
      betaSD_condition = 1, betaSD_tissue = 3, interceptMean = 4,
      interceptSD = 2, dispMeanRel = function(x) 4/x + 0.1,
      sizeFactors = rep(1, m))

### Arguments

`n` | number of rows (genes)
`m` | number of columns (samples)
`betaSD_condition` | the standard deviation for condition betas, i.e. beta ~ N(0,betaSD)
`betaSD_tissue` | the standard deviation for tissue betas, i.e. beta ~ N(0,betaSD)
`interceptMean` | the mean of the intercept betas (log2 scale)
`interceptSD` | the standard deviation of the intercept betas (log2 scale)
`dispMeanRel` | a function specifying the relationship of the dispersions on `2^trueIntercept`
`sizeFactors` | multiplicative factors for each sample

### Details

This function is designed and inspired following the proposal of `makeExampleDESeqDataSet` from the `DESeq2` package. Credits are given to Mike Love for the nice initial implementation

### Value

a `DESeqDataSet` with true dispersion, intercept for two factors (condition and tissue) and beta values in the metadata columns. Note that the true betas are provided on the log2 scale.

### Examples

    dds <- makeExampleDESeqDataSet_multifac(betaSD_condition = 3,betaSD_tissue = 1)
    dds
    dds2 <- makeExampleDESeqDataSet_multifac(betaSD_condition = 1,betaSD_tissue = 4)
    dds2

[Package pcaExplorer version 2.14.2 Index]