# Predicting and Classifying Patient Phenotypes with Multi-Omics Data

## Documentation for package ‘asmbPLS’ version 1.0.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## 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