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R: Simulate Data for Package Testing and Demonstration Purposes

simulateData

R Documentation

Simulate Data for Package Testing and Demonstration Purposes

Description

Simulate Data for Package Testing and Demonstration Purposes

Usage

  simulateData(nCols = 40, nRows = 1000, nEffectRows = 5, nNoEffectCols = 5,
      betweenClassDifference = 1, withinClassSd = 0.5)

Arguments

`nCols`	number of samples; currently this should be an even number
`nRows`	number of features (genes)
`nEffectRows`	number of differentially expressed features
`nNoEffectCols`	number of samples for which the profile of a differentially expressed feature will be set similar to the other class
`betweenClassDifference`	Average mean difference between the two classes to simulate a certain signal in the features for which an effect was introduced; the default is set to 1
`withinClassSd`	Within class standard deviation used to add a certain noise level to the features for which an effect was introduced; the default standard deviation is set to 0.5

Value

object of class ExpressionSet with the characteristics specified

Note

The simulation assumes the variances are equal between the two classes. Heterogeneity could easily be introduced in the simulation if this would be requested by the users.

Author(s)

W. Talloen and T. Verbeke

Examples

  someEset <- simulateData(nCols = 40, nRows = 1000, nEffectRows = 5, nNoEffectCols = 5)
  someEset

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(a4Core)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: glmnet
Loading required package: Matrix
Loading required package: foreach
Loaded glmnet 2.0-5

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/a4Core/simulateData.Rd_%03d_medium.png", width=480, height=480)
> ### Name: simulateData
> ### Title: Simulate Data for Package Testing and Demonstration Purposes
> ### Aliases: simulateData
> ### Keywords: manip
> 
> ### ** Examples
> 
>   someEset <- simulateData(nCols = 40, nRows = 1000, nEffectRows = 5, nNoEffectCols = 5)
>   someEset
ExpressionSet (storageMode: lockedEnvironment)
assayData: 1000 features, 40 samples 
  element names: exprs 
protocolData: none
phenoData
  sampleNames: Sample1 Sample2 ... Sample40 (40 total)
  varLabels: type
  varMetadata: type labelDescription
featureData: none
experimentData: use 'experimentData(object)'
Annotation:  
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>