mixOmics (version 2.8-1)

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, axis.labelX = TRUE, axis.labelY = TRUE,
	 type = c("combine", "separate"), col = jet.colors(64))

Arguments

X

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

Y

numeric matrix or data frame $(n \times q)$, the observations on the $Y$ variables. NAs are allowed.

axis.labelX

logical, should the name of each data on the axis X be shown ?

axis.labelY

logical, should the name of each data on the axis Y be shown ?

type

character string, (partially) maching one of "combine" or "separated", determining the kind of plots to be produced. See Details.

col

vector of colors such as that generated by heat.colors, topo.colors, rainbow or similar fun

encoding

latin1

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 the same 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. The estimation of the missing values can be performed by the reconstitution of the data matrix using the nipals function. Otherwise, missing values are handled by casewise deletion in the imaCor function. If axis.labelX = FALSE, the name of each data on the axis X is hidden. Default value is TRUE. If axis.labelY = FALSE, the name of each data on the axis Y is hidden. Default value is TRUE.

See Also

cor, image, jet.colors.

Examples

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

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

## 'separate' type plot
imgCor(X, Y, type = "separate")

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