R: Simulate differentially expressed gene pattern

make_DEG_pattern {Corbi} | R Documentation

## Simulate differentially expressed gene pattern

### Description

Generate complicated differentially expressed gene (DEG) pattern to simulate varied degree of heterogeneity.

### Usage

    make_DEG_pattern(
      n.genes,
      n.samples,
      fold.change = 2,
      gene.rate = 0.3,
      sample.rate = 1,
      active.rate = 1,
      up.rate = 0.5
    )

### Arguments

`n.genes` | The total number of genes in the simulated data.
`n.samples` | The total number of samples in the simulated data.
`fold.change` | The fold change level of DEGs.
`gene.rate` | The proportion of DEGs to all genes.
`sample.rate` | The proportion of abnormal samples to all samples.
`active.rate` | The probability that a DEG is truely differentially expressed in an abnormal sample.
`up.rate` | The proportion of up-regulated DEGs to all DEGs.

### Details

The heterogeneity of gene expression pattern is mainly controlled by two parameters: `sample.rate` and `active.rate`. If both parameters are equal to 1, the gene expression pattern will be homogeneous, otherwise heterogeneous.

### Value

This function will return a list with the following components:

`FC` | The matrix of simulated fold changes. Each row represents a gene and each column represents a sample.
`gene` | The vector of gene status: 1 for up-regulated, -1 for down-regulated, and 0 for normal genes.
`sample` | The vector of sample status: 1 for abnormal, and 0 for normal samples.

[Package Corbi version 0.6-1 Index]