[BioC] All equal high p-values from limma topTable . What to do ? Need help...

[Björn Usadel]

Hi Giulio,

in my limited and humble understanding
it means, that there are no genes which are called significantly changed 
after adjusting the p-values for multiple testing  using 
Benjamini-Hochberg fdr control.

This can have several reasons one of them being bad reproducibility. Did 
you also do some quality control as detailed in the user's guide? 
(looking at the background, considering M vs A plots etc. )
With this you might be able to trace down a "bad" array. But explaining 
is always difficult. Did your partners do some platform validation to 
see how good the platform is, how good it is in their hands etc. ? Maybe 
you can even make out some dye effect.

You can maybe compare your results with the swirl example for which you 
can download the data and then compare step by step where you might have 
problems.

For diagnostics only you might also want to pass the parameter 
adjust.method="none" to toptable. This switches off correcting for 
multiple testing, and if even then there are not a lot of genes which 
have low p-values, something is probably very bad.


Cheers,
Björn


>Hi I'm looking at the results of an analysis on 4 S. Cerevisiae cDNA arrays, 
>(2 of these have a dye-swap).
>I followed the example in limma user's guide (that if I'm not wrong is 
>exactly my case).
>
>I obtain a topTable of genes of this type
>
>	Block	Row	Column	ID	Name	M	A	t	P.Value	B
>4030	30	11	11	YLR162W	:::::1:	1.624122241	6.560234285	4.467743568	0.997257765	-2.0502737
>1254	10	4	11	YDR166C	SEC5:::::1:	-0.56584704	5.143049435	-3.824556839	0.997257765	-2.61592631
>1113	9	4	1	YDR409W	:::::1:	1.016356426	4.282139218	3.988554403	0.997257765	-2.683464218
>2115	16	10	5	YKL209C	STE6:::::1:	-0.540528098	7.340027942	-3.533312325	0.997257765	-2.686586054
>5022	37	16	11	YPR070W	:::::1:	-0.493446684	6.765075537	-3.415141086	0.997257765	-2.77744221
>3642	27	14	3	YOL045W	:::::1:	-0.678996258	5.185557216	-3.448815561	0.997257765	-2.865258763
>1602	12	14	3	YNL253W	:::::1:	-0.542907069	6.019893924	-3.427152231	0.997257765	-2.880360788
>4177	31	13	1	YNL221C	POP1:::::1:	-0.49777162	6.787712846	-3.274291885	0.997257765	-2.8886384
>
>
>Where all the p-values are 0.997257765. I read in the topTable help  that 
>"if there is no good evidence for differential
>     expression in the experiment, that it is quite possible for all
>     the adjusted p-values to be large, even for all of them to be
>     equal to one."
>
>I'm quite astonished ... and now ?
>This fact implies that is not a good experiment ? Or that data were not well 
>preprocessed ? Or maybe that for that experiment there are no genes 
>significantly differently expressed ?
>
>I'm analyzing that data from a Biomolecular lab, and I don't know what to do 
>and how to explain this...
>
>I'll be very happy for any help or suggestion ... !!!!!
>
>Thanks in advance,
>
>Giulio...
>This
>
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