SCFA {SCFA} | R Documentation

## SCFA

### Description

The main function to perform subtyping. It takes a list of data matrices as the input and outputs the subtype for each patient.

### Usage

    SCFA(dataList, k = NULL, max.k = 5, ncores = 10L, seed = NULL)

### Arguments

`dataList` | List of data matrices. In each matrix, rows represent samples and columns represent genes/features.
`k` | Number of clusters, leave as default for auto detection.
`max.k` | Maximum number of cluster
`ncores` | Number of processor cores to use.
`seed` | Seed for reproducibility, you still need to use set.seed function for full reproducibility.

### Value

A numeric vector containing cluster assignment for each sample.

### Examples

    #Load example data (GBM dataset)
    data("GBM")
    #List of one matrix (microRNA data)
    dataList <- GBM$data
    #Survival information
    survival <- GBM$survival
    library(survival)
    #Generating subtyping result
    set.seed(1)
    subtype <- SCFA(dataList, seed = 1, ncores = 2L)
    #Perform survival analysis on the result
    coxFit <- coxph(Surv(time = Survival, event = Death) ~ as.factor(subtype), data = survival, ties="exact")
    coxP <- round(summary(coxFit)$sctest[3],digits = 20)
    print(coxP)

[Package SCFA version 1.2.0 Index]