# netClass: An R Package for Network-Based Biomarker Discovery

## Documentation for package ‘netClass’ version 1.2.1

- DESCRIPTION file.

## Help Pages

netClass-package | An R package for network-Based microarray Classification
ad.matrix | An adjacency matrix of a sample graph...
calc.diffusionKernelp | Computing the Random Walk Kernel matrix of network
classify.aep | Training and predicting using aepSVM (aepSVM) classification methods
classify.frsvm | Training and predicting using FrSVM
classify.hubc | Training and predicting using hub nodes classification methods
classify.pac | Training and predicting using PAC classification methods
classify.stsvm | Training and predicting using stSVM classification methods
cv.aep | Cross validation for aepSVM (aepSVM)
cv.frsvm | Cross validation for FrSVM
cv.hubc | Cross validation for hub nodes classification
cv.pac | Cross validation for Pathway Activities Classification(PAC)
cv.stsvm | Cross validation for smoothed t-statistic to select significant top ranked differential expressed genes
EN2SY | An list for mapping gene entre ids to symbol ids
expr | Two expression profile matrixs and their labels
getGeneRanking | Get gene ranking based on geneRank algorithm.
getGraphRank | Random walk kernel matrix smoothing t-statistic
Gs2 | An subgraph of hub nodes
netClass | An R package for network-Based microarray Classification
pGeneRANK | GeneRANK
pOfHubs | Computing p value of hubs using the permutation test
predictAep | Predicting the test tdata using aep trained model
predictFrsvm | Predicting the test data using frsvm trained model
predictHubc | Predicting the test data using hubc trained model
predictPac | Predicting the test data using pac trained model
predictStsvm | Predicting the test data using stsvm trained model
probeset2pathway | Generae a mean gene expression of genes of each pathway matrix
probeset2pathwayTrain | Search CROG in training data
probeset2pathwayTst | Applied CROG to testing data
train.aep | Training the data using aep methods
train.frsvm | Training the data using frsvm method
train.hubc | Predicting the data using hub nodes classification model
train.pac | Training the data using pac methods
train.stsvm | Training the data using stsvm methods