[BioC] limma interaction model example

[limmauser [guest]]

Can someone please explain the example given in the limma vignette on page 45. It is an example of the classic interaction model. There are two different scenarios that are shown here, one without setting up contrasts, and one with setting up contrasts.

My question is specifically regarding the adj. pvalues that are reported. The reported p-values are different for each scenario. Why is that? What is the p-value corresponding to in the first scenario? What is it corresponding to in the second scenario?

Here are the results from my data set for scenario 1:
ID X.Intercept.    density8       treatT density8.treatT  AveExpr        F      P.Value    adj.P.Val
8116520 8116520     13.62623  0.06169053  0.061607654     -0.03356050 13.67948 278969.1 2.031311e-37 1.919204e-33
7894098 7894098     13.87349 -0.10169570  0.042710084     -0.01660554 13.83984 276812.7 2.157184e-37 1.919204e-33
8153903 8153903     13.66958  0.05382805 -0.007617839     -0.02515061 13.68640 252543.6 4.391650e-37 1.919204e-33
8038086 8038086     13.65395  0.06105315  0.041262169     -0.06775548 13.68817 248358.7 4.998637e-37 1.919204e-33
8179174 8179174     13.51915 -0.03694281  0.001696369      0.04665425 13.51319 242354.9 6.042135e-37 1.919204e-33

When i set up the contrasts as shown in the example, and pull out info. for the first probeset id in the list above(8116520), the p-values are different:

ID TvsUinlowDensity TvsUinhighDensity       Diff  AveExpr        F   P.Value adj.P.Val
8116520 8116520       0.06160765        0.02804716 -0.0335605 13.67948 1.707745 0.2136743 0.3896945

I also have two conditions density and treatment. Any insight/clarification will be appreciated.

Thanks!


 -- output of sessionInfo(): 

R version 2.15.1 (2012-06-22)
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] limma_3.14.1           hugene10stv1cdf_2.11.0 AnnotationDbi_1.20.3   affy_1.36.0            Biobase_2.18.0        
[6] BiocGenerics_0.4.0    

loaded via a namespace (and not attached):
 [1] affyio_1.26.0         BiocInstaller_1.8.3   DBI_0.2-5             IRanges_1.16.4        parallel_2.15.1      
 [6] preprocessCore_1.20.0 RSQLite_0.11.2        stats4_2.15.1         tools_2.15.1          zlibbioc_1.4.0       


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