[BioC] Questions about multtest
Rafael A. Irizarry
ririzarr at jhsph.edu
Tue Feb 24 18:31:46 MET 2004
On Tue, 24 Feb 2004, Oosting, J. (PATH) wrote:
<SNIP>
> so I basically computed all p-values from the t.test also
>
> mytt<-function(x,cl){
> t.test(x[cl==0],x[cl==1])$p.val
> }
>
> pvals<-apply(data[,6:12],1,mytt,cl= c(0,0,0,1,1,1,1))
>
> Well, values turned out to be the same when doing this so I had to conclude
> there was no difference between my groups there
it should be pointed out that with just 3 reps the t-test is not a very
powerful test (low sensitivity). you might consider alternatives, such
as the one performed by SAM (in the siggenes library) or one of the many
implemented in limma.
>
>
> Keep in mind that the mt.maxT returns a sorted array with lowest p-values on
> top
>
> Jan
>
> >
> > I run:
> >
> > > t <- mt.teststat(data[,6:12], c(0,0,0,1,1,1,1), test="t")
> >
> > which calculates the t statistic for my data. The t
> > statistic for my first gene comes up as:
> >
> > > t[1]
> > [1] 40.60158
> >
> > Presumably, this is equivalent to me running t.test:
> >
> > > t.test(data[1,9:12], data[1,6:8], var.equal=FALSE,
> > alternative="two.sided")
> >
> > Welch Two Sample t-test
> >
> > data: data[1, 9:12] and data[1, 6:8]
> > t = 40.6016, df = 2, p-value = 0.0006061
> > alternative hypothesis: true difference in means is not equal to 0
> > 95 percent confidence interval:
> > 1.713804 2.120092
> > sample estimates:
> > mean of x mean of y
> > -1.596190e-15 -1.916948e+00
> >
> > So I want to know how I can get p-values for the t statistics
> > I have just calculated using mt.teststat.
> >
>
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