combine gene expression and phenotype data onto a ExpressionSet object

Description

Basically a wrapper for new('ExpressionSet',...), this function gathers gene expression and phenotype data, after having checked their compatibility.

Usage

createExpressionSet(exprs = new("matrix"), phenoData = new("AnnotatedDataFrame"), varMetadata = NULL, dimLabels = c("rowNames", "colNames"), featureData = NULL, experimentData = new("MIAME"), annotation = character(0), changeColumnsNames = TRUE, ...)

Arguments

Details

If changeColumnsNames is TRUE, then the procedure is the following: first one checks if phenoData contains a column named 'colNames'. If so, content will be used to rename exprs colums. On the other case, one uses combinations of phenoData columns to create new names. In any case, old columns names are stored within a column named 'oldcolnames' in the pData.

Value

An object of class ExpressionSet

Author(s)

Eric Lecoutre

See Also

ExpressionSet

Examples

# simulate expression data of 10 features (genes) measured in 4 samples
x <- matrix(rnorm(40), ncol = 4)
colnames(x) <- paste("sample", 1:4, sep = "_")
rownames(x) <- paste("feature", 1:10, sep = "_")

# simulate a phenodata with two variables
ToBePheno <- data.frame(Gender = rep(c('Male','Female'), 2), 
		Treatment = rep(c('Trt','Control'), each=2))
rownames(ToBePheno) <- paste("sample", 1:4, sep = "_")

eset <- createExpressionSet(exprs = x, phenoData = ToBePheno)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> library(a4Base)
Loading required package: grid
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: AnnotationDbi
Loading required package: stats4
Loading required package: IRanges
Loading required package: S4Vectors

Attaching package: 'S4Vectors'

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

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: annaffy
Loading required package: GO.db

Loading required package: KEGG.db

KEGG.db contains mappings based on older data because the original
  resource was removed from the the public domain before the most
  recent update was produced. This package should now be considered
  deprecated and future versions of Bioconductor may not have it
  available.  Users who want more current data are encouraged to look
  at the KEGGREST or reactome.db packages

Loading required package: mpm
Loading required package: MASS

Attaching package: 'MASS'

The following object is masked from 'package:AnnotationDbi':

    select

Loading required package: KernSmooth
KernSmooth 2.23 loaded
Copyright M. P. Wand 1997-2009

mpm version 1.0-22

Loading required package: genefilter

Attaching package: 'genefilter'

The following object is masked from 'package:MASS':

    area

Loading required package: limma

Attaching package: 'limma'

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    plotMA

Loading required package: multtest
Loading required package: glmnet
Loading required package: Matrix

Attaching package: 'Matrix'

The following object is masked from 'package:S4Vectors':

    expand

Loading required package: foreach
Loaded glmnet 2.0-5

Loading required package: a4Preproc
Loading required package: a4Core

Attaching package: 'a4Core'

The following object is masked from 'package:limma':

    topTable

Loading required package: gplots

Attaching package: 'gplots'

The following object is masked from 'package:multtest':

    wapply

The following object is masked from 'package:IRanges':

    space

The following object is masked from 'package:S4Vectors':

    space

The following object is masked from 'package:stats':

    lowess


a4Base version 1.20.0

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/a4Base/createExpressionSet.Rd_%03d_medium.png", width=480, height=480)
> ### Name: createExpressionSet
> ### Title: combine gene expression and phenotype data onto a ExpressionSet
> ###   object
> ### Aliases: createExpressionSet
> ### Keywords: data
> 
> ### ** Examples
> 
> # simulate expression data of 10 features (genes) measured in 4 samples
> x <- matrix(rnorm(40), ncol = 4)
> colnames(x) <- paste("sample", 1:4, sep = "_")
> rownames(x) <- paste("feature", 1:10, sep = "_")
> 
> # simulate a phenodata with two variables
> ToBePheno <- data.frame(Gender = rep(c('Male','Female'), 2), 
+ 		Treatment = rep(c('Trt','Control'), each=2))
> rownames(ToBePheno) <- paste("sample", 1:4, sep = "_")
> 
> eset <- createExpressionSet(exprs = x, phenoData = ToBePheno)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>