callNCW {ccml}

Calculate normalized consensus weight(NCW) matrix based on permutation.

Description

Calculate normalized consensus weight(NCW) matrix based on permutation.

Usage

callNCW(
  title = "",
  label,
  nperm = 10,
  ncore = 1,
  seedn = 100,
  stability = TRUE,
  plot = NULL
)

Arguments

title

A character value for output directory. Directory is created only if not existed. This title can be an abosulte or relative path.

label

A matrix or data frame of input labels, columns=different clustering results and rows are samples.

nperm

A integer value of the permutation numbers, or nperm=10(default), which means nperm*1000 times of permutation.

ncore

A integer value of cores to use, or ncore=1 (default). It's the input core numbers for the parallel computation in this package parallel.

seedn

A numerical value to set the start random seed for reproducible results, or seedn=100 (default). For every 1000 iteration, the seed will +1 to get repeat results.

stability

A logical value. Should estimate the stability of normalized consensus weight based on permutation numbers (default stability=TRUE), or not?

plot

character value. NULL(default) - print to screen, 'pdf', 'png', 'pngBMP' for bitmap png, helpful for large datasets, or 'pdf'. Input for randConsensusMatrix.

Value

A matrix of normalized consensus weights.

Examples

# load data
data(example_data)
label=example_data

# if plot is not NULL, results will be saved in "result_output" directory
title="result_output"


# run ncw
ncw<-callNCW(title=title,label=label,stability=TRUE,nperm=4,ncore=1)