Dear all,

I am trying to run a regression analysis on my microarray data using the
limma and all the genes are showing adjusted p-values lower than 10 ^ - 20,
which points me to some sort of major mistake on the code that I am writing
for this analysis.  I searched the limma user's guide and the Bioconductor
mail archive for explanations on how to run regressions on limma but could
not figure out what I was doing wrong from them.  The code that I am using
goes below and any help with it would be extremely appreciated.
Also, is it possible to get the r-squared values for each gene in the
analysis?

Thank you very much,

Artur Veloso
Masters in Marine Biology Candidate
College of Charleston, SC, USA

> concentrations
 [1]  9.020  1.740  0.960  9.740  2.460  1.810  1.478  1.380  2.760  0.860
[11]  2.520  3.950  5.210  1.090 26.760  1.670  0.860  1.340  7.500  5.380
> regression.design <- model.matrix(~log(concentrations))
> regression.design
   (Intercept) log(concentrations)
1            1          2.19944433
2            1          0.55388511
3            1         -0.04082199
4            1          2.27624112
5            1          0.90016135
6            1          0.59332685
7            1          0.39068982
8            1          0.32208350
9            1          1.01523068
10           1         -0.15082289
11           1          0.92425890
12           1          1.37371558
13           1          1.65057986
14           1          0.08617770
15           1          3.28690824
16           1          0.51282363
17           1         -0.15082289
18           1          0.29266961
19           1          2.01490302
20           1          1.68268837
attr(,"assign")
[1] 0 1
> dim(vsn.normalized)
[1] 12426    20
> data.correlation <- duplicateCorrelation(vsn.normalized,regression.design
,ndups=2,spacing=1)
> data.regression <- lmFit(vsn.normalized,regression.design
,ndups=2,spacing=1,correlation=data.correlation$consensus)
> tail(topTable(eBayes(data.regression),number=6200))
                                                                 ID
1808 CV133193 triacylglycerol lipase activity CV_HP_010_Plate_96_B8
5545                    CD648266 none CV_UNI_001_Plate_96_G6_bottom
5267     CV088280 integral to membrane CV_HP_009_Plate_96_D9_bottom
4055                    CV133023 none CV_HP_011_Plate_96_D11_bottom
5935                     CV132240 none CV_HP_004_Plate_96_C6_bottom
4392                    AJ565488 none CG_NS1_001_Plate_96_G5_bottom
     X.Intercept. log.concentrations.        F      P.Value
1808     11.87372          -0.0947231 250.6960 2.810474e-24
5545     13.32032           0.1710411 244.8938 4.447522e-24
5267     11.13640          -0.1087474 242.2680 5.492360e-24
4055     11.03485          -0.1456426 239.7445 6.740600e-24
5935     10.69073           0.9076729 235.8741 9.263810e-24
4392     11.59845          -0.7217251 234.0277 1.079942e-23
        adj.P.Val
1808 2.818640e-24
5545 4.459725e-24
5267 5.506541e-24
4055 6.756913e-24
5935 9.284731e-24
4392 1.082206e-23

> sessionInfo()
R version 2.6.1 (2007-11-26)
i386-pc-mingw32

locale:
LC_COLLATE=English_United States.1252;LC_CTYPE=English_United
States.1252;LC_MONETARY=English_United
States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252

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

other attached packages:
[1] statmod_1.3.3        vsn_3.2.1            affy_1.16.0
preprocessCore_1.0.0 affyio_1.6.1
[6] Biobase_1.16.2       limma_2.12.0

loaded via a namespace (and not attached):
[1] grid_2.6.1     lattice_0.17-2

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