[BioC] extracting top120 genes after SAM analysis

[Gregor Siegler]

Dear list,

I have encountered following problem and do not know how to solve it:

After processing my data with RMA and filtering genes, that are not of 
interest I have performed SAM analysis. Here are the steps I took:

cell <- ReadAffy()
RMAcell <- rma(cell)

after filtering my data set, I have the following:

filtered
Expression Set (exprSet) with
        2271 genes
        20 samples
                 phenoData object with 1 variables and 20 cases
         varLabels
                sample: arbitrary numbering

I now perform SAM anaylsis like this to extract the genes of interest (I 
want to have about 120 called genes):

cl <- c(0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1)

where 0 stands for the probes of group 0, 1 for the samples of group 1.

c <- seq(1.3, 1.36, 0.01)
sam(filtered, cl, delta=c, rand =123)
SAM Analysis for the Two-Class Unpaired Case Assuming Unequal Variances

   Delta    p0 False Called    FDR
1   1.30 0.464  7.44    127 0.0272
2   1.31 0.464  7.30    126 0.0269
3   1.32 0.464  6.71    120 0.0260
4   1.33 0.464  6.41    117 0.0254
5   1.34 0.464  5.50    109 0.0234
6   1.35 0.464  5.50    109 0.0234
7   1.36 0.464  5.07    103 0.0229

now I summarize my results for delta= 1.32 :

sumRMA <- summary(sam(filtered,cl, delta=1.32, rand=123))

and want to extract those 120 genes like this:

top120RMA<-filtered[sumRMA at row.sig.genes,]
top120RMA

Expression Set (exprSet) with
        0 genes
        20 samples
                 phenoData object with 1 variables and 20 cases
         varLabels
                sample: arbitrary numbering

but as you can see, my expression set contains 0 genes out of my 20 samples. 
If I try the same steps but with GCRMA instead of RMA, everything works out 
well (of course with a different value for delta).

Every kind of help would be very much appreciated.

Thanks in advance!

With best regards,
gregor