consensus.CIT: Build a consensus classification using the CIT method

In cit-bioinfo/BuildConsensus: Build a consensus classification from multiple classification methods

Description

Compare and cluster various classification systems using Cohen's Kappa.

Usage

consensus.CIT(annot.class, outdir, CohenKappa.cut = seq(0.1, 0.7, 0.1))

Arguments

annot.class	Dataframe of samples annotated according to the several classification systems to compare.
outdir	Path to the directory where to store plots and results. A new directory will be created if the supplied path does not exist.
CohenKappa.cut	Value of Cohen's Kappa to select significant associations.

Value

A list of length 3 containing the Cohen's Kappa measures for any pair of subtypes (CohenKappaMat), the corresponding network generated (graph), the cluster assignments (cl)

Author(s)

Aurélie Kamoun

Examples

## Not run: 
 #-- Using bladder cancer classes as example
 library(BuildConsensus)
 data(blca_class)
 
 cit_res <- consensus.CIT(blca_class, outdir = "CIT_res")

## End(Not run)

cit-bioinfo/BuildConsensus documentation built on Nov. 27, 2019, 11:29 a.m.