[BioC] dye swaps of technical replicates and variable numbers of replicate spots

Ramon Diaz-Uriarte rdiaz at cnio.es
Wed Aug 20 17:11:09 MEST 2003

Gordon, thanks a lot for your responses.

> I would not recommend either of the above, at least in conjunction with
> limma. If you take means or medians of spots, and the number of spots being
> averaged differs between genes, then this will invalidate the assumption
> used by ebayes that all residual standard deviations are exchangeable
> (because different genes will be estimated with different precisions). Also
> you can't adapt dupcor.series because dupcor.series is designed to
> estimated a common spatial correlation, and different genes will have
> different between-replicate correlations if they are irregularly spaced.

Thanks for pointing this out. I didn't think about it.

> It might not be ideal, but I would avoid averaging the within-array
> replicates and just treat all spots as corresponding to different genes.
> Then you can be very confident that you have a reliable result if the same
> gene comes up differentially expressed several times (from different
> locations on the array).

OK. Sounds reasonable; that's probably what we'll do.

> Yes, the design matrix that you propose should work in limma and will give
> you valid results. The random-effects lme approach that you mention above
> though is in principle even better. You could get the best possible results
> by taking output from lme and inputing it in the right way into ebayes.
> (This is the obvious way to handle technical replicates, but I haven't seen
> anyone do it yet.)

I might try it then; all the input required by ebayes is all in the lme output 
and I'd just need to reorganize it.

Thanks again.


More information about the Bioconductor mailing list