imgCor: Image Maps of Correlation Matrices between two Data Sets
In mixOmics: Omics Data Integration Project

Description Usage Arguments Details Author(s) See Also Examples

Display two-dimensional visualizations (image maps) of the correlation matrices within and between two data sets.

imgCor(X,
Y,
type = "combine",
X.var.names = TRUE,
Y.var.names = TRUE,
sideColors = TRUE,
interactive.dev = TRUE,
title = TRUE,
color, row.cex, col.cex,symkey, keysize,
xlab, ylab, margins, lhei, lwid)

`X`	numeric matrix or data frame (n x p), the observations on the X variables. `NA`s are allowed.
`Y`	numeric matrix or data frame (n x q), the observations on the Y variables. `NA`s are allowed.
`type`	character string, (partially) maching one of `"combine"` or `"separated"`, determining the kind of plots to be produced. See Details.
`X.var.names, Y.var.names`	logical, should the name of X- and/or Y-variables be shown? If `TRUE` (defaults) `object$names$X` and/or `object$names$Y` are used. Possible character vector with X- and/or Y-variable labels to use.
`sideColors`	character vector of length two. The color name for horizontal and vertical side bars that may be used to annotate the X and Y correlation matrices.
`interactive.dev`	boolean. The current graphics device that will be opened is interactive?
`title`	logical, should the main titles be shown?
`color,xlab, ylab`	arguments passed to `cim`.
`row.cex, col.cex`	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.
`symkey`	boolean indicating whether the color key should be made symmetric about 0. Defaults to `TRUE`.
`keysize`	positive numeric value indicating the size of the color key.
`margins`	numeric vector of length two containing the margins (see `par(mar)`) for column and row names respectively.
`lhei, lwid`	arguments passed to `layout` to divide the device up into two rows and two columns, with the row-heights `lhei` and the column-widths `lwid`.

If type="combine", the correlation matrix is computed of the combined matrices cbind(X, Y) and then plotted. If type="separate", three correlation matrices are computed, cor(X), cor(Y) and cor(X,Y) and plotted separately on a device. In both cases, a color correlation scales strip is plotted.

The correlation matrices are pre-processed before calling the image function in order to get, as in the numerical representation, the diagonal from upper-left corner to bottom-right one.

Missing values are handled by casewise deletion in the imgCor function.

If X.names = FALSE, the name of each X-variable is hidden. Default value is TRUE.

If Y.names = FALSE, the name of each Y-variable is hidden. Default value is TRUE.

Ignacio González.

cor, image, color.jet.

data(nutrimouse)
X <- nutrimouse$lipid
Y <- nutrimouse$gene

## 'combine' type plot (default)
imgCor(X, Y)

## 'separate' type plot
## Not run: 
imgCor(X, Y, type = "separate")

## 'separate' type plot without the name of datas
imgCor(X, Y, X.names = FALSE, Y.names = FALSE, type = "separate")

## End(Not run)