mlp: Projection of points into one dimension.

Description Usage Arguments Details Value Author(s) Examples

Description

Project points onto the mean based line.

Usage

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## S4 method for signature 'Mlp'
getData(x, n = NULL)

## S4 method for signature 'Mlp'
initialize(.Object, ..., classes, points.orig, line,
  points.onedim, class.color)

## S4 method for signature 'Mlp,missing'
plot(x, y, steps = "all", ...)

mlp(mat, ...)

## S4 method for signature 'matrix'
mlp(mat, classes, class.color = NULL, ...)

## S4 method for signature 'Mlp'
show(object)

Arguments

x

matrix object for the function mlp otherwise it is a Mlp object

n

data to extract from Mlp (NULL gives all)

.Object

internal object

...

additional arguments to pass on

classes

vector in same order as rows in matrix

points.orig

multidimensional points describing the original data

line

multidimensional points describing a line

points.onedim

a vector of points

class.color

user assigned group coloring scheme

y

default plot param, which should be set to NULL(default: NULL)

steps

1,2,3,4,5,6 or "all"

mat

matrix with samples on rows, PCs in columns. Ordered PCs, with PC1 to the left.

object

Mlp object

Details

Projection of the points onto a line between the mean of two groups. Mlp is the abbreviation for 'mean line projection'. The function accepts, at the moment, only two groups and two PCs at a time.

An object containing results from a mean line projection reduction to one dimension.

The group and the one dimensional points are the most important information to carry out a classification using the classify() function. As a help to illustrate the details of the dimension reduction, the information from some critical steps are stored in the object. To visually explore these there is a dedicated plot method for Mlp objects, use plot().

Value

The mlp function returns an object of class Mlp

Author(s)

Jesper R. Gadin and Jason T. Serviss

Examples

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#use demo data
data(mlpMatrix)
groups <- rownames(mlpMatrix)

#run function
prj <- mlp(mlpMatrix, groups)

#getData accessor
getData(prj)

#getData accessor specific
getData(prj, "line")

#plot result
plot(prj)

jasonserviss/ClusterSignificance documentation built on May 9, 2019, 5:56 p.m.