[BioC] VSN 2.2

[Hans-Ulrich Klein]

Hi all,

I noticed that the function "vsn2" is much slower than the function 
"vsn". Probably it is not a general problem, but at least for my dataset 
the difference in computation time  is remarkable:

 > vsnResG <- vsn(RG$G[subSet,1:5], strata=RG$genes$Block[subSet]);
vsn: 25727 x 5 matrix (48 strata). 100% done.

Finished after ~30s.

 > vsnFitG <- vsn2(RG$G[subSet,1:5], strata=RG$genes$Block[subSet])
vsn: 25727 x 5 matrix (48 strata).   100% done.

Finished after ~1h.


After transformation

 > Gvsn_new <- predict(vsnFitG, RG$G[subSet,1:5])
 > parsG <- preproc(description(vsnResG))$vsnParams
 > Gvsn_old <- vsnh(RG$G[subSet,1:5] + 0, parsG, 
strata=RG$genes$Block[subSet])

I checked that the variance is independet of the mean. And plotted the 
new versus the old glog intensities:

 > plot(Gvsn_new, Gvsn_old/log(2), pch=".")
 > abline(0,1, col="red")

Here, the plot shows a couple of "stripes" with slope 1 and different 
intercepts.
I uploaded the plot:
http://img504.imageshack.us/img504/4700/oldnewglogge0.png

I guess that the "stripes" are the 48 printtips (used to stratify the 
data). Thus, the different additive offsets should not influence further 
analysis (like limma).

Best wishes,
Hans-Ulrich