aqm.prepdata {arrayQualityMetrics}R Documentation

Generate an object aqmobj.prepdata to be called by the aqm functions.

Description

aqm.prepdata formats an ExpressionSet, an AffyBatch, a NChannelSet, or a BeadLevelList into a aqmobj.prepdata object which can be used as an input of the aqm functions.

Usage

## S4 method for signature 'ExpressionSet':
aqm.prepdata(expressionset, do.logtransform)

aqm.prepdata(expressionset, do.logtransform = TRUE)

## S4 method for signature 'AffyBatch':
aqm.prepdata(expressionset, do.logtransform)
## S4 method for signature 'NChannelSet':
aqm.prepdata(expressionset, do.logtransform)
## S4 method for signature 'BeadLevelList':
aqm.prepdata(expressionset, do.logtransform)
## S4 method for signature 'aqmOneCol':
aqm.prepdata(expressionset, do.logtransform)

Arguments

expressionset An object of class ExpressionSet for one colour non Affymetrix data, AffyBatch for Affymetrix data, NChannelSet for two colour arrays, or BeadLevelList for Illumina bead arrays.
do.logtransform TRUE or FALSE whether or not you want to log transform the data.

Value

An object of class aqmobj.prepdata.

Author(s)

Audrey Kauffmann <audrey@ebi.ac.uk>

See Also

aqmobj.prepdata, aqm.boxplot, aqm.density, aqm.heatmap, aqm.maplot, aqm.meansd, aqm.probesmap, aqm.spatial, aqm.spatialbg

Examples

    ## Load an example of a NChannelSet
    library(CCl4)
    data(CCl4)

    ## Normalization of CCl4 using vsn
    library(vsn)
    CCl4norm = justvsn(CCl4, subsample=2000)

    ## Add a column in the phenoData to annotate samples 
    cond = paste(pData(CCl4norm)$RIN.Cy3,pData(CCl4norm)$RIN.Cy5,sep="/")
    poor = grep(cond,pattern="2.5")
    medium = grep(cond,pattern="^5/|/5")
    good = grep(cond,pattern="9.7")
    cov = rep(0, length = nrow(pData(CCl4norm)))
    cov[good] = "Good"
    cov[medium] = "Medium"
    cov[poor] = "Poor"
    phenoData(CCl4norm)$RNAintegrity = cov

    ## Add X and Y columns in the featureData to allow spatial representations
    featureData(CCl4norm)$X = featureData(CCl4norm)$Row
    featureData(CCl4norm)$Y = featureData(CCl4norm)$Column

    ## Add a hasTarget column in the featureData to call aqm.probesmap
    featureData(CCl4norm)$hasTarget = (regexpr("^NM",
                                       featureData(CCl4norm)$Name)> 0)

    ## Prepare the data for aqm.xxx calls
    CCl4prep = aqm.prepdata(CCl4norm, do.logtransform = FALSE)

    ## Draw MA plots
    ma = aqm.maplot(dataprep = CCl4prep)
    class(ma)
    aqm.plot(ma)

    ## Draw heatmap making use of the RNAintegrity
    ## column of the phenoData
    hm = aqm.heatmap(expressionset = CCl4norm,
                     dataprep = CCl4prep,
                     intgroup = "RNAintegrity")
    class(hm)
    aqm.plot(hm)

    ## Draw probes mapping density curves making use of the hasTarget
    ## column of the featureData
    sp = aqm.spatial(expressionset = CCl4norm,
                     dataprep = CCl4prep,
                     scale = "Rank")
    class(sp)
    aqm.plot(sp)

    ## Draw probes mapping density curves making use of the hasTarget
    ## column of the featureData
    pm = aqm.probesmap(expressionset = CCl4norm, dataprep = CCl4prep)
    class(pm)
    aqm.plot(pm)


[Package arrayQualityMetrics version 2.2.3 Index]