.pls

Perform a PLS discriminant analysis

internal

Provides functions to do 'O2PLS-DA' analysis for multiple omics data integration.
The algorithm came from "O2-PLS, a two-block (X±Y) latent variable regression (LVR) method with an integral OSC filter"
which published by Johan Trygg and Svante Wold at 2003 <doi:10.1002/cem.775>.
'O2PLS' is a bidirectional multivariate regression method that aims to separate the covariance between
two data sets (it was recently extended to multiple data sets) (Löfstedt and Trygg, 2011 <doi:10.1002/cem.1388>; Löfstedt et al., 2012 <doi:10.1016/j.aca.2013.06.026>)
from the systematic sources of variance being specific for each data set separately.

Kai Guo

o2plsda

Multiomics Data Integration

Junguk Hur

Eva Feldman

.pls function

<dl><dt>X</dt>
<dd>a matrix of predictor variables.</dd>
<dt>Y</dt>
<dd>a single vector indicate the group</dd>
<dt>nc</dt>
<dd>the number of pls components .</dd>
<dt>cv</dt>
<dd>logical indicating whether cross-validation will be performed or not (suggest TRUE).</dd>
<dt>nr_folds</dt>
<dd>nr_folds Integer to indicate the folds for cross validation.
@return list with PLS results</dd></dl>

Arguments

Partial least squares discriminant analysis — .pls

<dl>

<dt>X</dt>
<dd>a matrix of predictor variables.</dd>


<dt>Y</dt>
<dd>a single vector indicate the group</dd>


<dt>nc</dt>
<dd>the number of pls components .</dd>


<dt>cv</dt>
<dd>logical indicating whether cross-validation will be performed or not (suggest TRUE).</dd>


<dt>nr_folds</dt>
<dd>nr_folds Integer to indicate the folds for cross validation.
@return list with PLS results</dd>

</dl>

.pls: Partial least squares discriminant analysis

Description

Usage

Arguments