qualVarAnalysis: Tests association between qualitative variables and...

In MineICA: Analysis of an ICA decomposition obtained on genomics data

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)

MineICA documentation built on Nov. 8, 2020, 5:35 p.m.