heatplot {made4}R Documentation

Draws heatmap with dendrograms.

Description

heatplot calls heatmap.2 using a red-green colour scheme by default. It also draws dendrograms of the cases and variables using correlation similarity metric and average linkage clustering as described by Eisen. heatplot is useful for a quick overview or exploratory analysis of data

Usage

heatplot(dataset, dend = c("both", "row", "column", "none"),  cols.default = TRUE, lowcol = "green", highcol = "red", scale="row",  classvec=NULL, classvec2=NULL,  ...)

Arguments

dataset a matrix, data.frame, exprSet or marrayRaw. If the input is gene expression data in a matrix or data.frame. The rows and columns are expected to contain the variables (genes) and cases (array samples) respectively.
dend A character indicating whether dendrograms should be drawn for both rows and columms "both", just rows "row" or column "column" or no dendrogram "none". Default is both.
cols.default Logical. Default is TRUE. Use blue-brown color scheme
lowcol, highcol Character indicating colours to be used for down and upregulated genes when drawing heatmap if the default colors are not used, that is cols.default = FALSE.
scale Default is row. Scale and center either "none","row", or "column")
classvec A factor or vector which describes the classes in columns or rows of the dataset. Default is NULL. If included, a color bar including the class of each column (array sample) or row (gene) will be drawn. It will automatically add to either the columns or row, depending if the length(as.character(classvec)) ==nrow(dataset) or ncol(dataset)
classvec2 A factor or vector which describes the classes in columns or rows of the dataset. Default is NULL. If included, a color bar including the class of each column (array sample) or row (gene) will be drawn. It will automatically add to either the columns or row, depending if the length(as.character(classvec)) ==nrow(dataset) or ncol(dataset)
... further arguments passed to or from other methods

Details

The hierarchical plot is produced using average linkage cluster analysis with a correlation metric distance. heatplot calls heatmap.2 in the R package gplots.

Value

Plots a heatmap with dendrogram of hierarchical cluster analysis

Note

Because Eisen et al., 1998 use green-red colours for the heatmap heatplot uses these by default however a blue-red or yellow-blue are easily obtained by changing lowcol and highcol

Author(s)

Aedin Culhane

References

Eisen MB, Spellman PT, Brown PO and Botstein D. (1998). Cluster Analysis and Display of Genome-Wide Expression Patterns. Proc Natl Acad Sci USA 95, 14863-8.

See Also

See also as hclust, heatmap and dendrogram

Examples

data(khan)

heatplot(khan$train[1:30,], cols.default=FALSE, lowcol="white", highcol="red")
heatplot(khan$train[1:26,], labCol = c(64:1), labRow=LETTERS[1:26])

heatplot(khan$train[1:26,], classvec=khan$train.classes)

if (require(ade4, quiet = TRUE)) {
res<-ord(khan$train, ord.nf=5)  # save 5 components from correspondence analysis
khan.coa = res$ord
}

# Provides a view of the components of the Correspondence analysis (gene projection) in the lines (row)
heatplot(khan.coa$li)    # first 5 components
heatplot(khan.coa$li, margins=c(4,20))  # Change the margin size. The default is c(5,5)

  
# Sample projection (columns)
# See that the difference between tissues and cell line samples are defined in the first axis.

heatplot(khan.coa$co,classvec2=khan$train.classes, cols.default=FALSE, lowcol="blue", dend="row", scale="none")


[Package made4 version 1.12.1 Index]