A list whose elements are vector of
sample names, these sample names must be available in
sampleNames(icaSet). The list should be indexed by
the name of the corresponding groups.
labGroups
A vector of group names, will be used to
add names to sampleByGroup if
names(samplesByGroup) is NULL.
icaSet
An object of class
IcaSet
keepComp
A subset of components available in
indComp(icaSet), if NULL (default) all components
are used
file
A pdf file
breaks
The number of breaks to be used in the
histograms
colSel
The colour of the histogram of the group of
interest, default is "red"
colAll
The colour of the global histogram, default
is "grey74"
resClus
A list containing the outputs of function
clusterSamplesByComp, which consists of
results of clustering applied to matrix A of argument
icaSet.
funClus
Specifies the clustering method used,
either "Mclust" or "kmeans". If
resClus is not missing, equals
resClus$funClus.
titlesup
Additional title for the histograms
...
Additional parameters for function
hist
Details
For each subgroup of samples this function plots their
positions within the histogram of the global sample
contributions.
The values of interest are the sample contributions
across the components, i.e across the columns
A(icaSet).
If argument resClus is not missing, the
association between the clusters and the sub-groups of
samples is tested using a chi-square test. The p-values
of these tests are available in the title of each plot.
Value
NULL
Author(s)
Anne Biton
See Also
hist,
IcaSet
Examples
## Not run:
## load an example of IcaSet
data(icaSetCarbayo)
## selection of sample groups according to annotations STAGE
samplesByGroup <- lapply(split(pData(icaSetCarbayo),pData(icaSetCarbayo)[c("STAGE")]), rownames)
# select groups including at least 2 samples
samplesByGroup <- samplesByGroup[which(unlist(lapply(samplesByGroup,length))>1)]
## clustering of samples according to A using Mclust imposing two Gaussian
resClus <- clusterSamplesByComp(icaSet=icaSetCarbayo,funClus="Mclust", nbClus=2, clusterOn="A")
## Plot positions of the groups in 5th component
pdf(file="stageOnIC5.pdf", height = 8.267717, width = 29.7/2.54, paper = 'a4r', title="stageOnIC5")
plotPosSamplesInComp(samplesByGroup=samplesByGroup, icaSet=icaSetCarbayo, funClus="Mclust",
resClus = resClus, keepComp=5)
dev.off()
## End(Not run)