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

Sean Davis sdavis2 at mail.nih.gov
Thu Mar 23 18:56:45 CET 2006




On 3/23/06 11:14 AM, "Giulio Di Giovanni" <perimessaggini at hotmail.com>
wrote:

> 
> 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 0.997257
> 765 -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 0.99725
> 7765 -2.686586054
> 5022 37 16 11 YPR070W :::::1: -0.493446684 6.765075537 -3.415141086 0.99725776
> 5 -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 0.997257
> 765 -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 ? 

Giulio,

These two questions can't be answered by p-values; they should be answered
by other means.  There are several packages for looking at array quality and
for preprocessing. 

> Or maybe that for that experiment there are no genes
> significantly differently expressed ?

That is a distinct possibility.  If there are not data quality issues and
your sample size is large enough, then perhaps there are not detectible
differences (although this doesn't mean that there ARE NOT differences, just
that you couldn't see them).

Sean



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