MAMA (version 2.2.1)

rank.genes: Rank genes

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

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)