rank.genes: Rank genes

In MAMA: Meta-Analysis of MicroArray

Description

Assigna ranks to gene names according to p-value and sign of test statistics

Usage

rank.genes(T, p)

Arguments

T	vector of test statistics with gene names in names
p	vector of p-values with gene names in names

Value

Data frame with ranks of gene names

Author(s)

Ivana Ihnatova

References

Zintzaras, E., Ioannidis, J.P.A 2008 Meta-analysis for ranked discovery datasets: Theoretical framework and empirical demonstration for microarrays, Computational Biology and Chemistry 32, 39-47

See Also

compute.RQ

Examples

## Not run: 
data(Singhdata)

#compute T-statistics and P-value
p1<-apply(Singhdata$esets[[1]],1,function(x) {t=t.test(x~Singhdata$classes[[1]], alternative="two.sided"); return(t$p.value) })
p2<-apply(Singhdata$esets[[2]],1,function(x) {t=t.test(x~Singhdata$classes[[2]], alternative="two.sided"); return(t$p.value) })
p3<-apply(Singhdata$esets[[3]],1,function(x) {t=t.test(x~Singhdata$classes[[3]], alternative="two.sided"); return(t$p.value) })
T1<-apply(Singhdata$esets[[1]],1,function(x) {t=t.test(x~Singhdata$classes[[1]], alternative="two.sided"); return(t$statistic) })
T2<-apply(Singhdata$esets[[2]],1,function(x) {t=t.test(x~Singhdata$classes[[2]], alternative="two.sided"); return(t$statistic) })
T3<-apply(Singhdata$esets[[3]],1,function(x) {t=t.test(x~Singhdata$classes[[3]], alternative="two.sided"); return(t$statistic) })

# Rank genes
rank1<-rank.genes(T1,p1)
rank2<-rank.genes(T2,p2)
rank3<-rank.genes(T3,p3)

## End(Not run) 

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