OPLSR: Orthogonal Partial Least Squares regression

In computational-metabolomics/structToolbox: Data processing & analysis tools for Metabolomics and other omics

Orthogonal Partial Least Squares regression

Description

OPLS splits a data matrix into two parts. One part contains information orthogonal to the input vector, and the other is non-orthogonal.

Usage

OPLSR(number_components = 2, factor_name, ...)

Arguments

number_components	(numeric, integer) The number of orthgonal components. The default is 2.
factor_name	(character) The name of a sample-meta column to use.
...	Additional slots and values passed to struct_class.

Value

A OPLSR object with the following output slots:

opls_model	(list)
filtered	(DatasetExperiment)
orthogonal	(DatasetExperiment)

Inheritance

A OPLSR object inherits the following struct classes:

⁠[OPLSR]⁠ >> ⁠[model]⁠ >> ⁠[struct_class]⁠

Examples

M = OPLSR(
      number_components = 2,
      factor_name = "V1")

M = OPLSR('number_components'=2,factor_name='Species')

computational-metabolomics/structToolbox documentation built on July 5, 2024, 12:18 p.m.