[BioC] Un-balanced dye-swaps and LIMMA

[Matthew Hannah]

Hi,

I have some questions regarding some cDNA array data I've been asked to look at.
The design is slightly different to the standard designs, in that independent
biological replicates (different plants within the same experiment) have been
hybridised to different arrays. Therefore there are biological dye-swaps but not
technical ones.
Array 1 - WT plant 1/Treated plant 1
Array 2 - Treated plant 2/WT plant 2
Array 3 - WT plant 3/Treated plant 3

Analysing these data using LIMMA, lmfit and ebayes (as in html manual) produces
some odd looking qq plots that I have some questions about. All analyses used
print-tip loess followed by quantile normalisation, with different BG correction.
BG- NONE - produces a normal looking single S-curved line, but both ends are the
same side of the 1/1 line.
BG-minimum - looks alright, although the extreme values at the upper end cross
back over the 1/1 line.
BG- subtract - the qq plot separates at both ends into 3 lines (presumably 1 for 
each array), which clearly isn't normal.

My question is whether these are likely to result from the unbalanced dye-swap or
the independent plant (rather than pooled) RNA used. More generally is it valid
to treat the individual channels of cDNA data in any way similar to single array 
data (like affy?) after quantile normalising between arrays, or will the between 
array differences always be too great? Also is it generally considered best to use 
local BG correction, or non-corrected values and then eliminate bad spots later.

Thanks,
Matt