[BioC] Timeseries loop design analysis using Limma or Maanova?

[James W. MacDonald]

Hi Pete,

Pete wrote:

> I'm not quite sure I understand your point here? I was going to treat this 
> as a simple dye swap experiment, ignoring time and comparing mutant to WT.
> Is this not a statistically valid approach? There are 3 independ mutant 
> samples compared in dyeswaps to the WT pool. I understand that there is no 
> biological replicate for the WT pool, however it is technically replicated 
> at the dyeswap level and cDNA synthesis level. The biological variation of 
> the WT population is not of immediate interest in this case, hence a pool 
> was used. Individual mutant samples were used instead of a pool, because 
> only a limited number of mutants were available.

You can certainly do something like this, but there are some caveats. 
First, by comparing WT to mutant and ignoring time you are essentially 
looking at a main effect that might not be of much interest (hence why 
would you make the effort to do a time series?). Usually a more 
interesting question is to look for genes that are differentially 
expressed between mutant and WT at particular times, which I assume is 
why Jenny said you have no replication.

Second, when you compare biological replicates to technical replicates 
you are underestimating the true variability of the WT samples, which 
may result in apparent significance where there may have been none had 
biological replicates been used for WT samples as well. This is usually 
only a problem when you try to validate the results (using new 
biologically replicated samples), if there are many genes that fail to 
validate. Since the validation step is usually much slower and 
laborious, decreasing the number of false positives in the microarray 
step is often worth the time and effort.

Best,

Jim


-- 
James W. MacDonald
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623