[BioC] Filter on Fold Change

[Quentin Anstee]

Dear List,
 
I have used the genefilter package to filter out uninformative probe sets
from my GCRMA normalised affy experiment as follows.
 
f1 <- kOverA(3,6)
f2 <- function(x) (IQR(x) > 0.5)
ff<-filterfun(f1,f2)
wh<-genefilter(esetGCRMA, ff)
mySubSet<-esetGCRMA[wh,]
 
I would also like to filter out those genes that have less than a 2-fold
change in expression between any two of my three study groups *before* I go
on to fit a linear model and test for significant differences. My aim is to
test as few genes as possible to minimise the effect of multiple testing
correction and as I will only follow-up those with at least a 2-fold change,
I would like to filter out the rest as soon as possible.
 
Please can you advise me whether this can be achieved with genefilter. Also,
any advice on how to script this would also be much appreciated - I have had
a look at the vignettes but can't find any that describe filtering on fold
change although I see from the list archives that it is commonly done.
 
Many thanks,
 
Quentin