aqm.prepdata {arrayQualityMetrics} | R Documentation |
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.
## 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)
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. |
An object of class aqmobj.prepdata
.
Audrey Kauffmann <audrey@ebi.ac.uk>
aqmobj.prepdata
, aqm.boxplot
, aqm.density
, aqm.heatmap
, aqm.maplot
, aqm.meansd
, aqm.probesmap
, aqm.spatial
, aqm.spatialbg
## 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)