# Sparse Multiple Canonical Correlation Network Analysis Tool ('SmCCNet')

## Documentation for package ‘SmCCNet’ version 2.0.6

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

## Help Pages

aggregateCVSingle | Aggregate and Save Cross-validation Result for Single-omics Analysis
classifierEval | Evaluation of Binary Classifier with Different Evaluation Metrics
dataPreprocess | preprocess a omics dataset before running omics SmCCNet
fastAutoSmCCNet | Automated SmCCNet to Streamline the SmCCNet Pipeline
getAbar | Calculate similarity matrix based on canonical weights.
getCanCorMulti | Canonical Correlation Value for SmCCA
getCanWeightsMulti | Get Canonical Weight SmCCA Algorithm (No Subsampling)
getOmicsModules | Extract Omics Modules based on Similarity Matrix.
getRobustWeightsMulti | Run Sparse multiple Canonical Correlation Analysis and Obtain Canonical Weights (with Subsampling)
getRobustWeightsMultiBinary | Run Sparse multiple Canonical Correlation Analysis and Obtain Canonical Weights (with Subsampling)
getRobustWeightsSingle | Single-omics SmCCA with Quantitative Phenotype
getRobustWeightsSingleBinary | Single-omics SmCCA with Binary Phenotype
networkPruning | Prunes Subnetwork and Return Final Pruned Subnetwork Module
scalingFactorInput | Scaling Factor Input Prompt
summarizeNetSHy | NetSHy Summarization Score
X1 | A synthetic mRNA expression dataset.
X2 | A synthetic miRNA expression dataset.
Y | A synthetic phenotype dataset.