heatmap: Creates heatmap array CGH objects
In aCGH: Classes and functions for Array Comparative Genomic Hybridization data

Description Usage Arguments Details Value References See Also Examples

Clusters samples and produces heatmapp of the observed log2ratios.

heatmap(x, imp = TRUE, Rowv = NA, Colv = NULL, distfun = dist,
        hclustfun = hclust, add.expr, symm = FALSE,
        revC = identical(Colv, "Rowv"), scale = "none",
        na.rm = TRUE, margins = c(5, 5), ColSideColors,
        RowSideColors, cexRow = 0.2 + 1 / log10(nr),
        cexCol = 0.2 + 1 / log10(nc), labRow = NULL,
        labCol = NULL, main = NULL, xlab = NULL, ylab = NULL,
        verbose = getOption("verbose"), methodR = "ward.D",
        methodC = "ward.D", zlm = c(-0.5, 0.5), ...)

`x`	object of the `aCGH` object
`imp`	logical variable indicating whether `log2.ratios.imputed` or `log2.ratios` slot of `aCGH` should be used. Defaults to imputed value (TRUE).
`Rowv`	determines if and how the row dendrogram should be computed and reordered. Either a 'dendrogram' or a vector of values used to reorder the row dendrogram or 'NA' to suppress any row dendrogram (and reordering) or by default, 'NULL'
`Colv`	determines if and how the column dendrogram should be reordered. Has the same 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'
`add.expr`	expression that will be evaluated after the call to 'image'. Can be used to add components to the plot.
`symm`	logical indicating if 'x' should be treated symmetrically; can only be true when 'x' is a square matrix.
`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.
`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.
`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.
`main, xlab, ylab`	main, x- and y-axis titles;
`verbose`	logical indicating if information should be printed.
`methodR`	method to use for clustering rows. defaults to "ward.D"
`methodC`	method to use for clustering columns. defaults to "ward.D"
`zlm`	all the values greater or equal than zlm are set to zlm - 0.01. a;; value less or equal to -zlm are set to -zlm + 0.01
`...`	additional arguments passed on to 'image', e.g., 'col' specifying the colors.

This function is almost identical to the heatmap in base R. The slight modifications are that (1) a user can specify clustering method for rows and columns; (2) all the values outside specified limits are floored to be 0.01 less than a limit; (3) default values are different. Note that using default option of imp (TRUE) produces nicer looking plots as all missing values are removed.

Invisibly, a list with components

`crowInd`	row index permutation vector as returned by `order.dendrogram`
`colInd`	row index permutation vector as returned by `order.dendrogram`

heatmap function in base R

aCGH clusterGenome

#default plotting method for the aCGH object
data(colorectal)
plot(colorectal)

#to produce smoother looking heatmap, use imp = T: this will use imputed
#slot of aCGH object

plot(colorectal, imp = TRUE)