[BioC] [limma] Strange results in contrasts with dye-swap

[mjonczyk at biol.uw.edu.pl]

Dear Gordon,

thank you for clarifying this issue.


> > Results:
> >
> > TEST WITHOUT DYE EFFECT
> >> summary(test.ug)
> >   c2 - k2 c4 - k4 c6 - k6 c8 - k8 c10 - k10 c12 - k12 c14 - k14
> > -1     115      96     377     141       263       175       265
> > 0    43082   43048   42326   42973     42694     42842     42752
> > 1      196     249     690     279       436       376       376
> >
> >
> > TEST WITH DYE EFFECT
> >> summary(test.ug.d)
> >      p2    p4    p6    p8   p10   p12   p14
> > -1   246   217   686   317   530   316   526
> > 0  42797 42755 41594 42530 42103 42446 42239
> > 1    350   421  1113   546   760   631   628
> >
> > TEST WITH DYE EFFECT AND CONTRAST FOR DYE EFFECT
> >> summary(test.ug.d2)
> >   DyeEffect    p2    p4    p6    p8   p10   p12   p14
> > -1      6660   452   402  1103   593   858   539   883
> > 0      30803 42353 42261 40659 41853 41359 41888 41564
> > 1       5930   588   730  1631   947  1176   966   946
> >

> The lesson here is that you should not include DyeEffect in decideTests() 
> with your other contrasts.  When using method="global", you should only 
> include contrasts that are closely comparable to one another, and about 
> which you will be making conclusions as a group.
> 
> > *OTHER QUESTIONS*
> > 1. Is second model (WITH DYE EFFECT) correct?
> 
> Fine.
> 
Ok, so I use this model and "global" method.
> 
> 
> > 4. Should I include biol-replication effect in analysis (as block)?
> 
> If the biol replicates seem to vary randomly, and are only slightly 
> different, then I would suggest that you enter them as a random effect 
> using block instead.  If there are large differences between the biol 
> reps, in particular if one rep is different to the others, then including 
> them in the design matrix as you have done is safer and probably better.

The second scenario is true in this experiment, from PCA I know that differences
between replications isn't negligible.
So replication effect is already included, just because in target frame (and
consequently design matrix) each combination of samples on array is repeated
four times?

Best regards,
Maciej
> > ________________________________________________________
> > Maciej Jończyk, MSc
> > Department of Plant Molecular Ecophysiology
> > Institute of Plant Experimental Biology
> > Faculty of Biology, University of Warsaw
> > 02-096 Warszawa, Miecznikowa
> > 1