| 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)