Hi,

I have run the commands below to get an analysis of differential
expressions in my Affymetrix arrays

#Prepare the design and contrast matrices for my comparisons of the three
groups in a loop-manner.
> design<- model.matrix(~0+factor(c(1,1,1,2,2,2,3,3,3)))
> colnames(design)<- c('GroupA', 'GroupB', 'GroupC')
> contrast.matrix<- makeContrasts(GroupB-GroupA, GroupC-GroupA,
GroupC-GroupB, levels=design)

#Check design and contrast matrices
> design
  GroupA GroupB GroupC
1      1      0      0
2      1      0      0
3      1      0      0
4      0      1      0
5      0      1      0
6      0      1      0
7      0      0      1
8      0      0      1
9      0      0      1
attr(,"assign")
[1] 1 1 1
attr(,"contrasts")
attr(,"contrasts")$`factor(c(1, 1, 1, 2, 2, 2, 3, 3, 3))`
[1] "contr.treatment"

> contrast.matrix
        Contrasts
Levels   GroupB - GroupA GroupC - GroupA GroupC - GroupB
  GroupA              -1              -1               0
  GroupB               1               0              -1
  GroupC               0               1               1

#Fitting the eset to to the design and contrast
> fit <- lmFit(exprs, design)
> fit2 <- contrasts.fit(fit, contrast.matrix)

#Computing the statistics
> fit2 <- eBayes(fit2)


Then I check the results with topTable and get the following columns in the
output
> topTable(fit2)
      GroupB...GroupA GroupC...GroupA GroupC...GroupB  AveExpr        F
 P.Value adj.P.Val
25031       2.3602203       2.4273830      0.06716267 5.021412 29.06509
7.844834e-05 0.9587773
12902      -0.4572897      -0.5680943     -0.11080467 7.516681 25.41608
1.365021e-04 0.9587773
7158       -0.4478660      -0.4296077      0.01825833 7.057833 23.48871
1.880100e-04 0.9587773
18358      -0.1002647       0.3304903      0.43075500 7.352807 22.78417
2.125096e-04 0.9587773
28768      -0.7695883      -1.3837750     -0.61418667 3.983044 22.47514
2.244612e-04 0.9587773
28820      -0.1708800      -0.9939680     -0.82308800 5.470826 18.25071
5.081473e-04 0.9587773
15238      -0.4850297      -0.4658157      0.01921400 7.071662 17.15191
6.440979e-04 0.9587773
24681      -0.3759717      -0.3486450      0.02732667 9.281578 16.47813
7.493077e-04 0.9587773
19246      -0.8675393      -0.5082140      0.35932533 8.123538 16.27776
7.845150e-04 0.9587773
28808       0.2601277       0.6909140      0.43078633 4.814602 16.21283
7.963487e-04 0.9587773

I want to export my results and write

> results <- decideTests(fit2)
> write.fit(fit2, results, "limma_results.txt", adjust="BH")

Now don't get the same columns as when using topTable which is quite
confusing. Why don't I get the FC for the comparisons between the different
groups as if I run topTable with the coef parameter ( "topTable(fit2,
coef=1)" )? The columns I get are the following

A

Coef.GroupB - GroupA
Coef.GroupC - GroupA
Coef.GroupC - GroupB

t.GroupB - GroupA
t.GroupC - GroupA
t.GroupC - GroupB

p.value.GroupB - GroupA
p.value.GroupC - GroupA
p.value.GroupC - GroupB

p.value.adj.GroupB - GroupA
p.value.adj.GroupC - GroupA
p.value.adj.GroupC - GroupB

F
F.p.value

Res.GroupB - GroupA
Res.GroupC - GroupA
Res.GroupC - GroupB


Could some body please try to explain what do the columns A, Coef, F,
F.p.value and Res mean?



#Session info
> sessionInfo()
R version 2.15.0 (2012-03-30)
Platform: i386-pc-mingw32/i386 (32-bit)

locale:
[1] LC_COLLATE=Swedish_Sweden.1252  LC_CTYPE=Swedish_Sweden.1252
 LC_MONETARY=Swedish_Sweden.1252 LC_NUMERIC=C
 LC_TIME=Swedish_Sweden.1252

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

other attached packages:
[1] limma_3.12.1       Biobase_2.16.0     BiocGenerics_0.2.0

loaded via a namespace (and not attached):
[1] affylmGUI_1.30.0      IRanges_1.14.4        oneChannelGUI_1.22.10
stats4_2.15.0         tcltk_2.15.0
>

Best regards
JMA

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