heatmap.2 {gplots} | R Documentation |
A heat map is a false color image (basically
image(t(x))
) with a dendrogram added to the left side
and/or to the top. Typically, reordering of the rows and columns
according to some set of values (row or column means) within the
restrictions imposed by the dendrogram is carried out.
heatmap.2 (x, # dendrogram control Rowv = TRUE, Colv=if(symm)"Rowv" else TRUE, distfun = dist, hclustfun = hclust, dendrogram = c("both","row","column","none"), symm = FALSE, # data scaling scale = c("none","row", "column"), na.rm=TRUE, # image plot revC = identical(Colv, "Rowv"), add.expr, breaks, col="heat.colors", # block sepration colsep, rowsep, sepcolor="white", sepwidth=c(0.05,0.05), # cell labeling cellnote, notecex=1.0, notecol="cyan", na.color=par("bg"), # level trace trace=c("column","row","both","none"), tracecol="cyan", hline=median(breaks), vline=median(breaks), linecol=tracecol, # Row/Column Labeling margins = c(5, 5), ColSideColors, RowSideColors, cexRow = 0.2 + 1/log10(nr), cexCol = 0.2 + 1/log10(nc), labRow = NULL, labCol = NULL, # color key + density info key = TRUE, keysize = 1.5, density.info=c("histogram","density","none"), denscol=tracecol, #symkey = TRUE, # should be something like symkey = min(x < 0, na.rm=TRUE), densadj = 0.25, # plot labels main = NULL, xlab = NULL, ylab = NULL, # plot layout lmat = NULL, lhei = NULL, lwid = NULL, # extras ... )
x |
numeric matrix of the values to be plotted. |
Rowv |
determines if and how the row dendrogram should be
reordered. By default, it is TRUE, which implies dendrogram is
computed and reordered based on row means. If NULL or FALSE, then no
dendrogram is computed and no reordering is done. If a
dendrogram , then it is used "as-is", ie
without any reordering. If a vector of integers, then dendrogram is
computed and reordered based on the order of the vector. |
Colv |
determines if and how the column dendrogram should be
reordered. Has the options as the Rowv argument above and
additionally when x is a square matrix, Colv =
"Rowv" means that columns should be treated identically to the rows. |
distfun |
function used to compute the distance (dissimilarity)
between both rows and columns. Defaults to dist . |
hclustfun |
function used to compute the hierarchical clustering
when Rowv or Colv are not dendrograms. Defaults to
hclust . |
dendrogram |
character string indicating whether to draw 'none', 'row', 'column' or 'both' dendrograms. Defaults to 'both'. However, if Rowv (or Colv) is FALSE or NULL and dendrogram is 'both', then a warning is issued and Rowv (or Colv) arguments are honoured. |
symm |
logical indicating if x should be treated
symmetrically; can only be true when x is a square matrix. |
scale |
character indicating if the values should be centered and
scaled in either the row direction or the column direction, or
none. The default is "row" if symm false, and
"none" otherwise. |
na.rm |
logical indicating whether NA 's should be removed. |
revC |
logical indicating if the column order should be
rev ersed for plotting, such that e.g., for the
symmetric case, the symmetry axis is as usual. |
add.expr |
expression that will be evaluated after the call to
image . Can be used to add components to the plot. |
breaks |
(optional) Either a numeric vector indicating the
splitting points for binning x into colors, or a integer
number of break points to be used, in which case the break points
will be spaced equally between min(x) and max(x) . |
col |
colors used for the image. Defaults to heat colors
(heat.colors ). |
colsep, rowsep, sepcolor |
(optional) vector of integers indicating
which columns or rows should be separated from the preceding columns
or rows by a narrow space of color sepcolor . |
sepwidth |
(optional) Vector of length 2 giving the width (colsep) or height (rowsep) the separator box
drawn by colsep and rowsep as a function of the width (colsep) or
height (rowsep) of a cell. Defaults to c(0.05, 0.05) |
cellnote |
(optional) matrix of character strings which will be placed within each color cell, e.g. p-value symbols. |
notecex |
(optional) numeric scaling factor for cellnote
items. |
notecol |
(optional) character string specifying the color for
cellnote text. Defaults to "green". |
na.color |
Color to use for missing value (NA ). Defaults
to the plot background color. |
trace |
character string indicating whether a solid "trace" line should be drawn across 'row's or down 'column's, 'both' or 'none'. The distance of the line from the center of each color-cell is proportional to the size of the measurement. Defaults to 'column'. |
tracecol |
character string giving the color for "trace" line. Defaults to "cyan". |
hline, vline, linecol |
Vector of values within cells where a
horizontal or vertical dotted line should be drawn. The color of
the line is controlled by linecol . Horizontal lines are only
plotted if trace is 'row' or 'both'. Vertical lines are only
drawn if trace 'column' or 'both'. hline and
vline default to the median of the breaks, linecol
defaults to the value of tracecol . |
margins |
numeric vector of length 2 containing the margins
(see par(mar= *) ) for column and row names, respectively. |
ColSideColors |
(optional) character vector of length ncol(x)
containing the color names for a horizontal side bar that may be used to
annotate the columns of x . |
RowSideColors |
(optional) character vector of length nrow(x)
containing the color names for a vertical side bar that may be used to
annotate the rows of x . |
cexRow, cexCol |
positive numbers, used as cex.axis in
for the row or column axis labeling. The defaults currently only
use number of rows or columns, respectively. |
labRow, labCol |
character vectors with row and column labels to
use; these default to rownames(x) or colnames(x) ,
respectively. |
key |
logical indicating whether a color-key should be shown. |
keysize |
numeric value indicating the size of the key |
density.info |
character string indicating whether to superimpose a 'histogram', a 'density' plot, or no plot ('none') on the color-key. |
denscol |
character string giving the color for the density
display specified by density.info , defaults to the same value
as tracecol . |
symkey |
Boolean indicating whether the color key should be
made symmetric about 0. Defaults to TRUE . |
densadj |
Numeric scaling value for tuning the kernel width when
a density plot is drawn on the color key. (See the adjust
parameter for the density function for details.) Defaults to
0.25. |
main, xlab, ylab |
main, x- and y-axis titles; defaults to none. |
lmat, lhei, lwid |
visual layout: position matrix, column height, column width. See below for details |
... |
additional arguments passed on to image |
If either Rowv
or Colv
are dendrograms they are honored
(and not reordered). Otherwise, dendrograms are computed as
dd <- as.dendrogram(hclustfun(distfun(X)))
where X
is
either x
or t(x)
.
If either is a vector (of “weights”) then the appropriate
dendrogram is reordered according to the supplied values subject to
the constraints imposed by the dendrogram, by reorder(dd,
Rowv)
, in the row case.
If either is missing, as by default, then the ordering of the
corresponding dendrogram is by the mean value of the rows/columns,
i.e., in the case of rows, Rowv <- rowMeans(x, na.rm=na.rm)
.
If either is NULL
, no reordering will be done for
the corresponding side.
If scale="row"
the rows are scaled to have mean
zero and standard deviation one. There is some empirical evidence
from genomic plotting that this is useful.
The default colors range from red to white (heat.colors
) and
are not pretty. Consider using enhancements such
as the RColorBrewer package,
http://cran.r-project.org/src/contrib/PACKAGES.html#RColorBrewer
to select better colors.
By default four components will be displayed in the plot. At the top
left is the color key, top right is the column dendogram, bottom left
is the row dendogram, bottom right is the image plot. When
RowSideColor or ColSideColor are provided, an additional row or column
is inserted in the appropriate location. This layout can be
overriden by specifiying appropriate values for lmat
,
lwid
, and lhei
. lmat
controls the relative
postition of each element, while lwid
controls the column
width, and lhei
controls the row height. See the help page for
layout
for details on how to use these
arguments.
Invisibly, a list with components
rowInd |
row index permutation vector as returned by
order.dendrogram . |
colInd |
column index permutation vector. |
The original rows and columns are reordered in any case to
match the dendrogram, e.g., the rows by
order.dendrogram(Rowv)
where Rowv
is the
(possibly reorder()
ed) row dendrogram.
heatmap.2()
uses layout
and draws the
image
in the lower right corner of a 2x2 layout.
Consequentially, it can not be used in a multi column/row
layout, i.e., when par(mfrow= *)
or (mfcol= *)
has been called.
Andy Liaw, original; R. Gentleman, M. Maechler, W. Huber, G. Warnes, revisions.
library(gplots) data(mtcars) x <- as.matrix(mtcars) rc <- rainbow(nrow(x), start=0, end=.3) cc <- rainbow(ncol(x), start=0, end=.3) heatmap.2(x) ## default - dendrogram plotted and reordering done. heatmap.2(x, dendrogram="none") ## no dendrogram plotted, but reordering done. heatmap.2(x, dendrogram="row") ## row dendrogram plotted and row reordering done. heatmap.2(x, dendrogram="col") ## col dendrogram plotted and col reordering done. heatmap.2(x, keysize=2) ## default - dendrogram plotted and reordering done. heatmap.2(x, Rowv=FALSE, dendrogram="both") ## generate warning! heatmap.2(x, Rowv=NULL, dendrogram="both") ## generate warning! heatmap.2(x, Colv=FALSE, dendrogram="both") ## generate warning! hv <- heatmap.2(x, col=cm.colors(256), scale="column", RowSideColors=rc, ColSideColors=cc, margin=c(5, 10), xlab="specification variables", ylab= "Car Models", main="heatmap(<Mtcars data>, ..., scale=\"column\")", tracecol="green", density="density") str(hv) # the two re-ordering index vectors data(attitude) round(Ca <- cor(attitude), 2) symnum(Ca) # simple graphic # with reorder heatmap.2(Ca, symm=TRUE, margin=c(6, 6), trace="none" ) # without reorder heatmap.2(Ca, Rowv=FALSE, symm=TRUE, margin=c(6, 6), trace="none" ) ## Place the color key below the image plot heatmap.2(x, lmat=rbind( c(0, 3), c(2,1), c(0,4) ), lhei=c(1.5, 4, 2 ) ) ## Place the color key to the top right of the image plot heatmap.2(x, lmat=rbind( c(0, 3, 4), c(2,1,0 ) ), lwid=c(1.5, 4, 2 ) ) ## For variable clustering, rather use distance based on cor(): data(USJudgeRatings) symnum( cU <- cor(USJudgeRatings) ) hU <- heatmap.2(cU, Rowv=FALSE, symm=TRUE, col=topo.colors(16), distfun=function(c) as.dist(1 - c), trace="none") ## The Correlation matrix with same reordering: hM <- format(round(cU, 2)) hM # now with the correlation matrix on the plot itself heatmap.2(cU, Rowv=FALSE, symm=TRUE, col=rev(heat.colors(16)), distfun=function(c) as.dist(1 - c), trace="none", cellnote=hM) ## genechip data examples ## Not run: library(affy) data(SpikeIn) pms <- SpikeIn@pm # just the data, scaled across rows heatmap.2(pms, col=rev(heat.colors(16)), main="SpikeIn@pm", xlab="Relative Concentration", ylab="Probeset", scale="row") # fold change vs "12.50" sample data <- pms / pms[, "12.50"] data <- ifelse(data>1, data, -1/data) heatmap.2(data, breaks=16, col=redgreen, tracecol="blue", main="SpikeIn@pm Fold Changes\nrelative to 12.50 sample", xlab="Relative Concentration", ylab="Probeset") ## End(Not run)