qualVarAnalysis {MineICA} | R Documentation

## Tests association between qualitative variables and components.

### Description

This function tests if the groups of samples formed by the variables are differently distributed on the components, in terms of contribution value (i.e of values in matrix `A(icaSet)`). The distribution of the samples on the components are represented using either density plots of boxplots. It is possible to restrict the tests and the plots to a subset of samples and/or components.

### Usage

      qualVarAnalysis(params, icaSet, keepVar,
        keepComp = indComp(icaSet),
        keepSamples = sampleNames(icaSet),
        adjustBy = c("none", "component", "variable"),
        method = "BH", doPlot = TRUE, typePlot = "density",
        addPoints = FALSE, onlySign = TRUE,
        cutoff = params["pvalCutoff"],
        colours = annot2col(params), path = "qualVarAnalysis/",
        filename = "qualVar", typeImage = "png")

### Arguments

`params` | An object of class `MineICAParams` providing the parameters of the analysis.
`icaSet` | An object of class `IcaSet`.
`keepVar` | The variable labels to be considered, must be a subset of `varLabels(icaSet)`.
`keepComp` | A subset of components, must be included in `indComp(icaSet)`. By default, all components are used.
`keepSamples` | A subset of samples, must be included in `sampleNames(icaSet)`. By default, all samples are used.
`adjustBy` | The way the p-values of the Wilcoxon and Kruskal-Wallis tests should be corrected for multiple testing: `"none"` if no p-value correction has to be done, `"component"` if the p-values have to be corrected by component, `"variable"` if the p-values have to be corrected by variable
`method` | The correction method, see `p.adjust` for details, default is `"BH"` for Benjamini & Hochberg.
`doPlot` | If TRUE (default), the plots are done, else only tests are performed.
`addPoints` | If TRUE, points are superimposed on the boxplot.
`typePlot` | The type of plot, either `"density"` or `"boxplot"`.
`onlySign` | If TRUE (default), only the significant results are plotted.
`cutoff` | A threshold p-value for statistical significance.
`colours` | A vector of colours indexed by the variable levels, if missing the colours are automatically generated using `annot2Color`.
`path` | A directory _within resPath(params)_ where the files containing the plots and the p-value results will be located. Default is `"qualVarAnalysis/"`.
`typeImage` | The type of image file to be used.
`filename` | The name of the HTML file containing the p-values of the tests, if NULL no file is created.

### Details

This function writes an HTML file containing the results of the tests as a an array of dimensions 'variables * components' containing the p-values of the tests. When a p-value is considered as significant according to the threshold `cutoff`, it is written in bold and filled with a link pointing to the corresponding plot. One image is created by plot and located into the sub-directory "plots/" of `path`. Each image is named by index-of-component_var.png. Wilcoxon or Kruskal-Wallis tests are performed depending on the number of groups of interest in the considered variable (argument `keepLev`).

### Value

Returns A data.frame of dimensions 'components x variables' containing the p-values of the non-parametric tests (Wilcoxon or Kruskal-Wallis tests) wich test if the samples groups defined by each variable are differently distributed on the components.

### Author(s)

Anne Biton

### See Also

, `qualVarAnalysis`, `p.adjust`, `link{writeHtmlResTestsByAnnot}`, `wilcox.test`, `kruskal.test`

### Examples

    ## load an example of IcaSet
    data(icaSetCarbayo)

    ## build MineICAParams object
    params <- buildMineICAParams(resPath="carbayo/")

    ## Define the directory containing the results
    dir <- paste(resPath(params), "comp2annot/", sep="")

    ## Run tests, make no adjustment of the p-values,
    # for variable grade and components 1 and 2,
    # and plot boxplots when 'doPlot=TRUE'.
    qualVarAnalysis(params=params, icaSet=icaSetCarbayo, adjustBy="none", typePlot="boxplot",
                    keepVar="GRADE", keepComp=1:2, path=dir, doPlot=FALSE)

[Package MineICA version 1.26.0 Index]