goodAndPoorClassification: Function to classify the unsupervised clusters found through...
In geneSignatureFinder: A Gene-signatures finder tools

Description Usage Arguments Details Value Author(s) Examples

This function label the groups found by the unsupervised classification in good and poor.

1	goodAndPoorClassification(clustering)

clustering

factor of so many elements as the number of samples containing the classification in two groups. Missing values are allowed.

The labelling of the two groups in good and poor is obtained through the comparion of the expected and the observed failures computed in the test statistics of the log-rank test. The group for which the expected are more than the observed are classified are good prognosis. The variable stData has to be defined in the environment.

A factor with levels "good" and "poor".

Stefano M. Pagnotta, Michele Ceccarelli and Pietro Zoppoli

data(geNSCLC)
geData <- geNSCLC

data(stNSCLC)
stData <- stNSCLC
######################
randomClustering  <- runif(nrow(stData)) > .5
survdiff(stData ~ randomClustering)
###############
clusteringByPrognosis <- goodAndPoorClassification(randomClustering)
survdiff(stData ~ clusteringByPrognosis)