Predicting and Classifying Patient Phenotypes with Multi-Omics Data

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Documentation for package ‘asmbPLS’ version 1.0.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

asmbPLS-package	Predicting and Classifying Patient Phenotypes with Multi-Omics Data
asmbPLS	Predicting and Classifying Patient Phenotypes with Multi-Omics Data
asmbPLS.cv	Cross-validation for asmbPLS to find the best combinations of quantiles for prediction
asmbPLS.example	Example data for asmbPLS algorithm
asmbPLS.fit	asmbPLS for block-structured data
asmbPLS.predict	Using an asmbPLS model for prediction of new samples
asmbPLSDA.cv	Cross-validation for asmbPLS-DA to find the best combinations of quantiles for classification
asmbPLSDA.example	Example data for asmbPLS-DA algorithm
asmbPLSDA.fit	asmbPLS-DA for block-structured data
asmbPLSDA.predict	Using an asmbPLS-DA model for classification of new samples
asmbPLSDA.vote.fit	asmbPLS-DA vote model fit
asmbPLSDA.vote.predict	Using an asmbPLS-DA vote model for classification of new samples
mbPLS.fit	mbPLS for block-structured data
meanimp	Mean imputation for the survival time
plotCor	Graphical output for the asmbPLS-DA framework
plotPLS	PLS plot for asmbPLS-DA
plotRelevance	Relevance plot for asmbPLS-DA
quantileComb	Create the quantile combination set for asmbPLS and asmbPLS-DA
to.categorical	Converts a class vector to a binary class matrix