plotPosAnnotInComp: Histograms of sample contributions for each annotation level
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 groups of samples formed by the variables (i.e the sample annotations) across all the components of an object of class icaSet. For each variable level (e.g for each tumor stage) this function plots the positions of the corresponding samples (e.g the subset of samples having this tumor stage) within the histogram of the global sample contributions. The plots are saved in pdf file, one file is created per variable. The pdf files are names 'variable.pdf' and save either in pathPlot if specified or the current directory.

  plotPosAnnotInComp(icaSet, params,
    keepVar = varLabels(icaSet),
    keepComp = indComp(icaSet),
    keepSamples = sampleNames(icaSet), pathPlot = NULL,
    breaks = 20, colAll = "grey74", colSel, resClus,
    funClus = c("Mclust", "kmeans"), nbClus = 2,
    by = c("annot", "component"),
    typeImage = c("pdf", "png", "none"), ...)

`icaSet`	An object of class `IcaSet`
`params`	A `MineICAParams` object
`keepVar`	The variable labels to be considered, i.e a subset of the column labels of the pheno data of icaSet available in (`varLabels(icaSet)`)
`keepComp`	A subset of components available in `indComp(icaSet)`; by default, all components are used
`keepSamples`	A subset of samples, must be available in `sampleNames(icaSet)`; by default, all samples are used
`pathPlot`	A character specifying the path where the plots will be saved
`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 sample clustering applied to matrix A of argument `icaSet`. If missing, the clustering is performed by the function.
`funClus`	The clustering method to be used, either `"Mclust"` or `"kmeans"`. If `resClus` is not missing, equals `resClus$funClus`.
`nbClus`	If `resClus` is missing, it provides the number of clusters to be computed by `funClus`, default is 2
`by`	Either `"annot"` to plot the histograms of each variable across all components, or `"component"` to plot the histograms for each component across variables. When `by="annot"` one pdf file is created by variable name, while when `annot="component"`, one pdf file is created by component.
`typeImage`	The type of image to be created, either "pdf" (default) or "png". "png" is not recommended, unless there are at the most 4 histograms to be plotted, because it does not allow to deal with multiple pages of plots.
`...`	Additional parameters for function `hist`

The plotted values are the sample contributions across the components, i.e across the columns of A(icaSet).

If argument resClus is missing, the function computes the clustering of the samples on each component (i.e on each column of A(icaSet)) using funClus and nbClus.

The association between the clusters and the considered sample group is tested using a chi-square test. The p-values of these tests are available in the title of each plot.

When by="annot" this function plots the histograms of each variable across all components, to plot the histograms for each component across variables, please use by="component".

NULL

Anne Biton

plotPosSamplesInComp, chisq.test

## Not run: 
## load an example of IcaSet
data(icaSetCarbayo)

## Use icaSetCarbayo, look at the available annotations
varLabels(icaSetCarbayo)

## Plot positions of samples in components according to annotations 'SEX' and 'STAGE'
# plots are saved in files SEX.pdf and STAGE.pdf created in the current directory
plotPosAnnotInComp(icaSet=icaSetCarbayo, keepVar=c("SEX","STAGE"), keepComp=1:2,  funClus="Mclust")
# specifiy arg 'pathPlot' to save the pdf in another directory, but make sure it exists before
# specifiy arg 'by="comp"' to create one pdf file per component

## End(Not run)