[BioC] Pooling in microarray studies

[Kenny Ye]

>From a study I have done on affymatrix chips (HU95A). the pooled sample
does reproduce the average of individual samples. I haven't got
time to write the paper. but I will be happen to sent you the data that
demonstrate this. By pooling, the biological variation are averaged, the
only power you lose is from the technical variation, which is quite low
with affymatrix chips. 

As I know, similar but larger studies on pooling is undergone at U. Of Wisconsin
on mice and rats. I expect the similar results will be shown.

Pooling, however, is more suitable for mice studies(animal in general)
than human, as the mices being pooled are often similar from same strain.
Also, pooling should have some other advantage in your case as 
the signal/noise ratio should be higher for pooled sample (more RNA)
compared to the individuals. 

Kenny

Kenny Ye
Assistant Professor
Department of Applied Math and Statistics
SUNY at  Stony Brook
Stony Brook, New York 11794-3600
Phone (631)632-9344
Fax   (631)632-8490

On Mon, 6 Oct 2003, Wiesner Vos wrote:

> 
> Thanks for the replies Min-han and Jim.
> I suspected that this may be the case (keeping the
> papers in mind about comparing expression measures
> on the Dilution data eg. Cope et al.)
> 
> I suspected that the use 8ug would be perhaps
> not make much of a difference if you use
> an expression measure like for example
> RMA that seems to be reasonably independent of
> the actual amount of RNA on a chip. Thanks
> again for your help.
> 
> 
> 
> Wiesner J. Vos
> Department of Statistics
> University of Oxford
> 1 South Parks Road
> OX1 3TG
> United Kingdom
> 
> 
> 
> 
> 
> 
> On Mon, 6 Oct 2003, Tan, MinHan wrote:
> 
> > - Perhaps it is an policy issue with your microarray core facility, but
> > the standard Affymetrix GeneChip Technical Manual recommends 5 - 20 ug
> > total RNA.
> >
> > - I routinely use 5 ug total RNA with no apparent problems.
> >
> > - So yes, you should be able to do single sample hybridizations.
> >
> > Regards,
> > Min-Han
> >
> >
> >
> > -----Original Message-----
> > From: Wiesner Vos [mailto:vos at stats.ox.ac.uk]
> > Sent: Monday, October 06, 2003 9:27 AM
> > To: bioconductor at stat.math.ethz.ch
> > Subject: [BioC] Pooling in microarray studies
> >
> >
> >
> > I have question arising to the pooling of mRNA
> > samples. Someone approached me about the
> > following problem:
> >
> > The study wants to use Affymetrix chips to study
> > changes in expression between a group of treated
> > mice and a group untreated mice. There are 10 mice
> > in each group. It is only possible to extract
> > 8 ug of RNA from each mouse, not enough for one chip. (According to the
> > experimenters they require 10 ug per
> > chip)  So it is not possible to use biological
> > replicate chips for each individual mice. Now the issue
> > is whether to perhaps pool the RNA in each group
> > and carry out analysis on technical replicates from the
> > pooled samples.
> >
> > As I understand it pooling may reduce the precision, with
> > the risk that one or few samples can dominate the outcome, and that
> > averaging over single sample hybridisations is perhaps safer than using
> > pooled samples. However in this case you cannot do single sample
> > hybridisations.
> >
> > I was wondering if the following approach is an acceptable compromise to
> > retain at least some information on the between sample variation in each
> > group:
> >
> > Mix the RNA from 2 different mice on a single chip to get 5
> > hybridisations, where the hybridisation on each chip is from the mix of
> > the RNA samples of two mice? I though that this may enable you to some
> > extend if all the mice are behaving similarly. Ofcourse one would not be
> > able to distinguish between the behaviour of the two mice relating to
> > the same chip. Or is it better to accept that you do not have enough RNA
> > to hybridize the sample for each individual to a separate chip and pool
> > the samples and accept the risk that one sample may dominate the
> > outcome? The best solution did not seem obvious (to me at least!)
> >
> > Any comments will be much appreciated.
> >
> > Wiesner
> >
> >
> >
> > Wiesner J. Vos
> > Department of Statistics
> > University of Oxford
> > 1 South Parks Road
> > OX1 3TG
> > United Kingdom
> >
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