phenoTest (version 1.20.0)

ClusterPhenoTest: Test association of clusters with phenotype.

Description

Test the associations between clusters that each sample belongs to (based on gene expression) and each phenotype.

Usage

ClusterPhenoTest(x,cluster,vars2test,B=10^4,p.adjust.method='none')

Arguments

x

ExpressionSet with phenotype information stored in pData(x).

cluster

variable of class character or factor telling at which cluster each sample belongs to.

vars2test

list with components 'continuous', 'categorical', 'ordinal' and 'survival' indicating which phenotype variables should be tested. 'continuous', 'categorical' and 'ordinal' must be character vectors, 'survival' a matrix with columns named 'time' and 'event'. The names must match names in names(pData(x)).

B

An integer specifying the number of replicates used in the chi-square Monte Carlo test (passed on to chisq.test).

p.adjust.method

Method for P-value adjustment, passed on to p.adjust.

Details

Test association between the provided clusters and each phenotype. For variables in vars2test\$continuous and vars2test\$ordinal a Kruskal-Wallis Rank Sum test is used; for vars2test\$categorical a chi-square test (with exact p-value if simulate.p.value is set to TRUE); for var2test\$survival a Cox proportional hazards likelihood-ratio test.

Examples

#load data
data(eset)  
eset

#construct vars2test
survival <- matrix(c("Relapse","Months2Relapse"),ncol=2,byrow=TRUE)
colnames(survival) <- c('event','time')
#add positive to have more than one category
pData(eset)[1:20,'lymph.node.status'] <- 'positive' 
vars2test <- list(survival=survival,categorical='lymph.node.status')
vars2test

#first half of the samples will be one cluster and the rest the other cluster
cluster <- c(rep('Cluster1',floor(ncol(eset)/2)),rep('Cluster2',ncol(eset)-floor(ncol(eset)/2)))

#test association
ClusterPhenoTest(eset,cluster,vars2test=vars2test)