[BioC] nsFilter and GSEA

[Paolo Innocenti]

Hi again,

I tried with a different normalisation method, and I was pretty 
surprised by the results:

 > eset.mas <- mas5(mydata)
background correction: mas
PM/MM correction : mas
expression values: mas
background correcting...done.
14010 ids to be processed
|                    |
|####################|
 > eset.mas.f <- nsFilter(eset.mas)
 > eset.mas.f$filter.log
$numDupsRemoved
[1] 1098

$numLowVar
[1] 1

$feature.exclude
[1] 3

$numRemoved.ENTREZID
[1] 786

 > eset.rma <- rma(mydata)
Background correcting
Normalizing
Calculating Expression
 > eset.rma.f <- nsFilter(eset.rma)
 > eset.rma.f$filter.log
$numDupsRemoved
[1] 3

$numLowVar
[1] 13047

$feature.exclude
[1] 3

$numRemoved.ENTREZID
[1] 786

 > dim(eset.rma.f$eset)
Features  Samples
      171       15
 > dim(eset.mas.f$eset)
Features  Samples
    12122       15

I don't understand how is it possible. Any suggestion about what to do? 
Should I lower the cutoff for the rma, or that processing method doesn't 
work for my dataset?

Paolo
PS: I tried also a really low cutoff, but the situation doesn't change, 
unless I choose a cutoff=0.1:

 > eset.filter <- nsFilter(eset,var.cutoff=0.2)
 > eset.filter$filter.log
$numDupsRemoved
[1] 69

$numLowVar
[1] 10560

$feature.exclude
[1] 3

$numRemoved.ENTREZID
[1] 786