computeOrdering: Function to compute ordered gene lists

In MAMA: Meta-Analysis of MicroArray

Description

Function computes test statistic for each gene in each dataset of MetaArray object and orders them form the most up-regulated (possitive statisics) to the most down-regulated (negative statistics).

Usage

computeOrdering(data, varname, test)

Arguments

data	MetaArray object
varname	A string indicating which column of clinical data matrices should be used to compute test statistic. Same column is used in all datasets.
test	"FCH" for fold change (function fold.change) or "T" for T-test (function meta.test)

Value

A data frame, each column refers to ordered gene list from one study

Author(s)

Ivana Ihnatova

See Also

fold.change, meta.test

Examples

data(Singhdata)

cl1<-as.data.frame(Singhdata$classes[[1]])
names(cl1)<-"classlab"
cl2<-as.data.frame(Singhdata$classes[[2]])
names(cl2)<-"classlab"
cl3<-as.data.frame(Singhdata$classes[[3]])
names(cl3)<-"classlab"
rownames(Singhdata$esets[[1]])<-Singhdata$geneNames
rownames(Singhdata$esets[[2]])<-Singhdata$geneNames
rownames(Singhdata$esets[[3]])<-Singhdata$geneNames

data<-new("MetaArray", GEDM=list(Singhdata$esets[[1]], Singhdata$esets[[2]], Singhdata$esets[[3]]),
clinical=list(cl1, cl2, cl3), datanames=c("dataset1", "dataset2", "dataset3"))

ord<-computeOrdering(data, "classlab", "FCH")

MAMA documentation built on Jan. 15, 2017, 3:05 p.m.