dummyData {bumphunter} | R Documentation

## Generate dummy data for use with bumphunter functions

### Description

This function generates a small dummy dataset representing samples from two different groups (cases and controls) that is used in bumphunter examples.

### Usage

    dummyData(n1 = 5, n2 = 5, sd = 0.2, l = 100, spacing = 100,
              clusterSpacing=1e5, numClusters=5)

### Arguments

`n1` | Number of samples in group 1 (controls)
`n2` | Number of samples in group 2 (cases)
`sd` | Within group standard deviation to be used when simulating data
`l` | The number of genomic locations for which to simulate data
`spacing` | The average spacing between locations. The actual locations have a random component so the actual spacing will be non-uniform
`clusterSpacing` | The spacing between clusters. (Specifically, the spacing between the first location in each cluster.)
`numClusters` | Divide the genomic locations into this number of clusters, each of which will contain locations spaced `spacing` bp apart.

### Value

A list containing data that can be used with various bumphunter functions.

`mat` | A simulated data matrix with rows representing genomic locations and columns representing samples.
`design` | Design matrix with rows representing samples and columns representing covariates.
`chr` | A character vector with the chromosomes of each location.
`pos` | A numeric vector representing the chromosomal position.
`cluster` | A vector representing the cluster of each locations
`n1` | Number of samples in cluster 1
`n2` | Number of samples in cluster 2

### Author(s)

Martin J. Aryee

### Examples

    dat <- dummyData()
    names(dat)
    head(dat$pos)

[Package bumphunter version 1.22.0 Index]