Hi Eleni,

Check *"Computing Thousands of Test Statistics Simultaneously in R"  *in
http://stat-computing.org/newsletter/v181.pdf

Other alternative could be the multtest package.


HTH

Jorge



On Wed, Mar 5, 2008 at 8:55 AM, Eleni Christodoulou <[EMAIL PROTECTED]>
wrote:

> On Wed, Mar 5, 2008 at 2:05 PM, ian white <[EMAIL PROTECTED]> wrote:
>
> > Don't you need to make some allowance for multiple testing? E.g. to get
> > a experiment-wise significance level of 0.01 you need
> >
> > which(p.values < very small number)
> >
> > where the very small number is approximately 0.01/(total number of
> > genes).
> >
> > On Wed, 2008-03-05 at 14:38 +0200, Eleni Christodoulou wrote:
> > > I am sorry, the test is unpaired...But my question remains
> > >
> > > Thanks,
> > > Eleni
> > >
> > > On Wed, Mar 5, 2008 at 2:33 PM, Eleni Christodoulou <
> [EMAIL PROTECTED]
> > >
> > > wrote:
> > >
> > > > Hello list,
> > > >
> > > > I am trying to apply the paired t.test between diseased and not
> > diseased
> > > > patients to identify genes that are more expressed in the one
> > situation
> > > > under the other. In order to retrieve the genes that are more
> > expressed in
> > > > the positive disease state I do:
> > > > p.values<-c()
> > > > for(i in 1:length(Significant[,1])){
> > > > p.values[i]<-try(t.test(positive[i,],negative[i,],alternative
> > > > ="greater")$p.value)
> > > > }
> > > >
> > > > which(p.values<0.01)
> > > >
> > > >
> > > > where Significant is my matrix of  genes  and their expression in
> > tumors
> > > > and positive, negative are subsets of thes matrix.
> > > > Whn p<0.01, I reject the null hypothesis and I accept the
> alternative
> > one,
> > > > that I have greater gene expression in positive than in negative.
> > > > I assume I must be doing sth wrong because the heatmap that I get
> with
> > the
> > > > genes that pass the filter of p-value is wrong.
> > > >
> > > > Could anyone help me with this?
> > > >
> > > > thanks a lot,
> > > > Eleni
>
>

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