heatplot {made4} | R Documentation |
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
heatplot(dataset, dend = c("both", "row", "column", "none"), cols.default = TRUE, lowcol = "green", highcol = "red", scale="row", classvec=NULL, classvec2=NULL, ...)
dataset |
a matrix , data.frame ,
ExpressionSet 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. |
The hierarchical plot is produced using average linkage cluster analysis with a
correlation metric distance. heatplot
calls heatmap.2
in the R package gplots
.
Plots a heatmap with dendrogram of hierarchical cluster analysis
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
Aedin Culhane
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 as hclust
,
heatmap
and dendrogram
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")