mixOmics (version 6.3.2)

imgCor: Image Maps of Correlation Matrices between two Data Sets

Description

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

Usage

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)

Arguments

X

numeric matrix or data frame $(n$ x $p)$, the observations on the $X$ variables. NAs are allowed.

Y

numeric matrix or data frame $(n$ x $q)$, the observations on the $Y$ variables. NAs 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.

Details

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.

See Also

cor, image, color.jet.

Examples

# NOT RUN {
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")
# }