[BioC] how to handle pooled replicate?

[Jianping Jin]

Dear Sean,

I really appreciated your comments and time!

best regards,

JP-


--On Tuesday, August 01, 2006 12:57 PM -0400 Sean Davis 
<sdavis2 at mail.nih.gov> wrote:

>
>
>
> On 8/1/06 12:42 PM, "Jianping Jin" <jjin at email.unc.edu> wrote:
>
>> Dear Sean,
>>
>> Thanks for your comments! Are you saying a data set with technical
>> replicates only, like this one, is not appropriate for any limma model,
>> or even regular t-test? This was the concern I had in my first help
>> request.
>
> The question that one asks with t-tests (or variants) is if the magnitude
> of the change (mean) is outside that expected by chance given the
> variation in the measurements.  By variation, one usually means
> "biologic" variation. Since you have no biologic replicates, you cannot
> really estimate the biologic variation, only some form of technical
> variation, upon which your t-testing strategy will be based.  It is
> "valid", but the interpretation is not the usual based on biologic
> replicates.
>
>> Actually the lab researchers conducted RT-PCR, in which they used two
>> strategies that may improve the uncertainty caused due to lack of
>> biological replicates in microarray assay. One was that they used samples
>> that were from separate mice relative to ones for microarray. Secondly
>> they selected genes with at least 2-fold change in gene expression for
>> PCR verification. The results were pretty consistent between microarray
>> and RT-PCR. Can genes with more than 2-fold change in expression avoid
>> possible dye effect in general?
>
> I would say that dye effect is, in general, not huge in terms of
> magnitude, but I would still be concerned about results without
> validation, but it seems your lab collaborator is willing to do that.
>
> Sean
>



##################################
Jianping Jin Ph.D.
Bioinformatics scientist
Center for Bioinformatics
Room 3133 Bioinformatics building
CB# 7104
University of Chapel Hill
Chapel Hill, NC 27599
Phone: (919)843-6105
FAX:   (919)843-3103
E-Mail: jjin at email.unc.edu