Hi Donglei & James


Thanks for your reply.  I am sorry for not making myself clear. I already
have this matrix that contains Probeset    p-value (strain effect) p-value
(treatment effect) p-value (interaction).  As you suggested, I can use
pvalue cut-off to select probesets for strain effect. From the selected list
(for strain effect), I would like to choose probsets that are significant
for Strain A and then for Strain B.  In the same way, I would like to select
probesets for Treatment A and Treatment B.

I hope, this explains my problem.
Thanks again,
Sharon


On 1/5/06, donghu@itsa.ucsf.edu <donghu@itsa.ucsf.edu> wrote:
>
> Hi,
>
> You can make a matrix which has 4 columns:
>
> Probeset    p-value (strain effect) p-value (treatment effect) p-value
> (interaction)
>
> Then you can select probe sets based on these p-values.
>
> Hope this helps.
>
> Donglei Hu
>
> On Thu, 5 Jan 2006 15:26:15 +0100 Sharon wrote:
>
> >  Hi All,
> >
> > I am trying to analyze affy data for strain, treatment and their
> > interaction
> > effects (RMA normalized, log2 expression values). The design looks like
> >
> >    strain A --> treatment 1       strain B --> treatment 1
> >                     treatment 2                         treatment 2
> >
> > so, I used anova(aov(expra ~ strain + treatment + strain*treatment, m)),
> > where m <- data.frame(strain, treatment, expr)
> >
> > I have got the corresponding pvalues for strain, treatment & interaction
> > effects( this for all the probsets).  Now, I would like to separate the
> > number of significant probesets for strain A and strain B from strain
> > effect
> > (I would like to do the same for treatment effect).  How can I do
> > this? Any
> > help is very much appreciated.
> >
> > Thanks in Advance.
> > Regards,
> >  Sharon
> >
> >       [[alternative HTML version deleted]]
> >
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> >
>
>
>

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