494 Statistics and Data Analysis for Microarrays Using R and Bioconductor
+ controls = x[labels=="control"]
+ p=t.test( tumors, controls,var.equal=TRUE)$p.value
+ foldchange=mean(tumors)-mean(controls)
+ c(foldchange,p)
+ }
> results=t(apply(data,1,mytest))
> rownames(results)<-rownames(data)
> colnames(results)<-c("logFC","p")
> results<-results[order(results[,2]),]
> results
logFC p
g17 -1.2425105 0.02109769
g15 -1.7077999 0.02664108
g8 0.8294332 0.05353653
g18 0.7093357 0.05961968
g13 -0.6270931 0.13584092
g16 1.0850587 0.13736632
g1 0.5179938 0.13742521
g14 0.9814332 0.16142621
g20 -1.1525251 0.22673566
g10 -0.5467774 0.25337128
g5 0.5955697 0.26985110
g3 -0.4736879 0.28613640
g11 -0.3490123 0.31418421
g6 0.4571497 0.35606553
g7 0.2056308 0.48526338
g2 0.37608