SimilarityNetworkFusion {MBMethPred}

Similarity network fusion (SNF)

Description

A function to perform SNF function (from SNFtool package) and output clusters.

Usage

SimilarityNetworkFusion(
  Files = NULL,
  NNeighbors,
  Sigma,
  NClusters,
  CLabels = NULL,
  RLabels = NULL,
  Niterations
)

Arguments

Files

A list of data frames created using the ReadSNFData function or matrices.

NNeighbors

The number of nearest neighbors.

Sigma

The variance for local model.

NClusters

The number of clusters.

CLabels

A string vector to name the clusters. Optional.

RLabels

The actual label of samples to calculate the Normalized Mutual Information (NMI) score. Optional.

Niterations

The number of iterations for the diffusion process.

Value

Factor

Examples

data(RLabels) # Real labels
data(Data2) # Methylation
data(Data3) # Gene expression
snf <- SimilarityNetworkFusion(Files = list(Data2, Data3),
                               NNeighbors  = 13,
                               Sigma = 0.75,
                               NClusters = 4,
                               CLabels = c("Group4", "SHH", "WNT", "Group3"),
                               RLabels = RLabels,
                               Niterations = 10)
snf