Hi guys,

 

although this is probably no problem concerning analysis maybe some of you
have an idea what might be going wrong here.

 

We are observing a strange problem with GeneST Arrays from Affymetrix.
Independent from the experiment design and number of arrays we hardly
observe any differentially expressed genes using the "gene level" analysis.
Maybe one to five genes if many and that would be without any multiple
testing correction. Even genes we know that they are regulated  or even
knocked out don't display any significant change. And we are talking about
cell culture experiments in some cases. Switching to "exon level" returns
some more candidates and our knowledge about the experiment tells us they
might be true positives but by the regulation strength and total number of
regulated candidates they might as well be false positives due to the much
higher number of probesets.

 

Now the issue worrying us is, that we performed several smaller studies with
the GeneST arrays know, mouse AND human, and didn't get a single study yet
with remarkable results. We never observed such problems with the "old"
human and murine whole genome arrays and all we get to hear from Affymetrix
is ".well other groups report the GeneSTs are running much better and more
sensitive than the old chips.and they are more robust .".

 

I don't think the statistical part is making the problems because we tried
normalization with RMA and PLIER (I didn't try VSN yet, maybe I should try
that) and I would expect a simple non-corrected Welch test and a screening
of potential targets by eye-balling to find at least a bunch of hits. But no
chance. And we are sticking to the standard kits and protocol from
Affymetrix in the lab. I already had a chat with the guys from Charite and
Max-Planck in Berlin and from the Affymetrix Core Facility in Kiel, Germany.
They are all doing just the same thing and getting nice results. We couldn't
find a step we are doing significantly different on computer or in lab.

 

So what I am interested in is: Does anybody of guys with experience with the
GeneST arrays have an idea what might be causing the problem on our side,
either already in lab or afterwards in the analysis? 

 

Best regards,

 

Benjamin

 

 

PS: I know the best step to go forward from here is performing the same
experiment on one of the old whole genome and on GeneST in parallel to check
the result. Still maybe somebody has an idea before we start with that.

 

 

___________________________________________

Benjamin Otto, PhD

University Medical Center Hamburg-Eppendorf

Institute For Clinical Chemistry

Campus Forschung N27

Martinistr. 52,

D-20246 Hamburg

 

Tel.: +49 40 7410 51908

Fax.: +49 40 7410 54971

___________________________________________

 



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