[BioC] Dye-swap Design
Naomi Altman
naomi at stat.psu.edu
Tue Nov 3 14:07:22 CET 2009
1. Biological dye-swaps are fine.
2. It depends on whether there is a strong dye effect. Given my own
experience, I think the dye effect observed by Churchill and Kerr,
which was limited to a couple of probes, was real, but that much of
the more pervasive effect reported by others can be attributed to
technical problems with the dyes. So, carefully handled arrays, with
dye protectorants, which not have much dye effect.
3. The pooled samples have smaller biological variance than the other
samples. If the variance is dominated by technical variance (e.g. in
an inbred species) your solution is reasonable. If it is dominated
by biological variance, then you are artificially reducing the
variance estimate that is used for your statistical tests.
Regards,
Naomi
At 10:58 AM 11/2/2009, Jason Pear wrote:
>Dear Listers,
>
>
>
>We have a case-control study and would like to use Agilent 4x44K
>array. We only have three biological replicates. My questions are
>
>
>
>1. Do we need to use technical dye-swap or we can use biological
>dye-swap (budget issue)?
>
>
>
>2. How does the un-balanced dye-swap effect the analysis?
>
>
>
>3. If we use biological dye-swap and balanced dye-swap, since we
>only have three samples for each condition. Can we pool samples in
>order to balance dye-swap? Here is the design:
>
>
>
> Array1 Array2
> Array3 Array4
>
>Red caseA controlB
>caseC pooled control
>
>Green controlA caseB
>controlC pooled case
>
>
>
>Many thanks,
>
>
>
>Jason
>
>
>
>_________________________________________________________________
>Hotmail: Trusted email with Microsoft's powerful SPAM protection.
>
>
>
> [[alternative HTML version deleted]]
>
>_______________________________________________
>Bioconductor mailing list
>Bioconductor at stat.math.ethz.ch
>https://stat.ethz.ch/mailman/listinfo/bioconductor
>Search the archives:
>http://news.gmane.org/gmane.science.biology.informatics.conductor
Naomi S. Altman 814-865-3791 (voice)
Associate Professor
Dept. of Statistics 814-863-7114 (fax)
Penn State University 814-865-1348 (Statistics)
University Park, PA 16802-2111
More information about the Bioconductor
mailing list