plotPLS {asmbPLS}

PLS plot for asmbPLS-DA

Description

Function to visualize cluster of samples using super score of different PLS components.

Usage

plotPLS(fit.results, comp.X = 1, comp.Y = 2, group.name = NULL, legend = TRUE)

Arguments

fit.results

The output of asmbPLSDA.fit.

comp.X

A integer indicating which PLS component to be used for the X.axis. The default is 1.

comp.Y

A integer indicating which PLS component to be used for the Y.axis. The default is 2.

group.name

A vector containing the named character for each sample group. For binary outcome, first group name matches Y.matrix = 0, second group name matches Y.matrix = 1. For multiclass outcome, ith group name matches ith column of Y.matrix = 1.

legend

A logical value indicating whether the legend should be added. The default is TRUE.

Details

The function returns a plot to show cluster of samples using super score of different PLS components.

Value

none

Examples

## Use the example dataset
data(asmbPLSDA.example)
X.matrix = asmbPLSDA.example$X.matrix
Y.matrix.binary = asmbPLSDA.example$Y.matrix.binary
Y.matrix.multiclass = asmbPLSDA.example$Y.matrix.morethan2levels
X.dim = asmbPLSDA.example$X.dim
PLS.comp = asmbPLSDA.example$PLS.comp
quantile.comb = asmbPLSDA.example$quantile.comb
 
## asmbPLSDA fit for binary outcome
asmbPLSDA.fit.binary <- asmbPLSDA.fit(X.matrix = X.matrix, 
                                      Y.matrix = Y.matrix.binary, 
                                      PLS.comp = PLS.comp, 
                                      X.dim = X.dim, 
                                      quantile.comb = quantile.comb,
                                      outcome.type = "binary")

## asmbPLSDA fit for categorical outcome with more than 2 levels
asmbPLSDA.fit.multiclass <- asmbPLSDA.fit(X.matrix = X.matrix, 
                                          Y.matrix = Y.matrix.multiclass,
                                          PLS.comp = PLS.comp, 
                                          X.dim = X.dim, 
                                          quantile.comb = quantile.comb,
                                          outcome.type = "multiclass")

## visualization to show the cluster of samples using the first and the second super score
plotPLS(asmbPLSDA.fit.binary, comp.X = 1, comp.Y = 2)
plotPLS(asmbPLSDA.fit.multiclass, comp.X = 1, comp.Y = 2)
## custom group.name
plotPLS(asmbPLSDA.fit.binary, 
        comp.X = 1, 
        comp.Y = 2, 
        group.name = c("control", "case"))
plotPLS(asmbPLSDA.fit.multiclass, 
        comp.X = 1, 
        comp.Y = 2, 
        group.name = c("healthy", "mild", "severe"))