heatslide: Heatmap with dotplot like visualization of effect sizes

In floatofmath/bt88.03.704: floats MSI utility function

Heatmap with dotplot like visualization of effect sizes

Description

Draws a heatmap of a matrix (e.g. gene expression data) together with dotplots of a statistic (e.g. log fold change between experimental settings) for each line

Usage

heatslide(mat, stat, pheno, genenames = NULL,
  hcols = colorRampPalette(c("blue", "white", "red"))(32),
  lcols = rainbow(length(levels(pheno))), scaleValues = c("row", "column",
  "none"), scaler = "linear", slidetitle = "Log (Base 2) Foldchange",
  rowSort = TRUE, colSort = TRUE)

Arguments

mat	Matrix containing the values to be plotted in the heatmap
stat	Vector of values that should be plotted by the dotplot beside each line of the heatmap
pheno	Vector giving the group labels for each column of the matrix
genenames	Character vector giving genenames (or corresponding annotation)
hcols	Colours to be used in the heatmap
lcols	Colours to indicate the column labels
scaleValues	Scale expression values by either 'row', 'column', or 'none'
scaler	if "linear" use scale and remove mean and divide by sd, if "rank" transform to ranks
slidetitle	Text to be shown below the panel containing the dotplots
rowSort	if TRUE genes will be sorted according to the test statistic
colSort	if FALSE chips will be sorted according to the phenotype

Details

We call the dotplots ‘sliders’ because the faintly resemble sliders.

Author(s)

Florian Klinglmueller [e-mail]

Examples

    mat <- matrix(rnorm(120),ncol=6)
    stat <- rnorm(20)
    labels <- factor(rep(0,1,each=3))
    hcols <- gray.colors(32)
    lcols <- c('blue','red')

    heatslide(mat,stat,labels,hcols,lcols)

floatofmath/bt88.03.704 documentation built on March 25, 2022, 12:28 p.m.