plotPosSamplesInComp: Histograms of sample subsets
In MineICA: Analysis of an ICA decomposition obtained on genomics data

Description Usage Arguments Details Value Author(s) See Also Examples

This function plots the positions of several groups of samples across all the components of an icaSet object.

  plotPosSamplesInComp(samplesByGroup, labGroups = NULL,
    icaSet, keepComp = indComp(icaSet), file = NULL,
    breaks = 20, colAll = "grey74", colSel = "red",
    titlesup = "", resClus,
    funClus = c("Mclust", "kmeans"), ...)

`samplesByGroup`	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`

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.

NULL

Anne Biton

hist, IcaSet

## 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)