[BioC] PCR Validation threshold in dChip normalized data

[Benjamin Otto]

Hi Sean,

First, thanks for the quick reply!

Second, I wouldn't expect a perfect cutoff between possible validation and junk. That would be more a question about judging the data signal range with some tolerance where I can expect the gene to be expressed at all and where the bets are, that I don't see much more than a lot of noise.

Third, probably I was just a little bit too slow to attach my PS comment. What irritated and animated me to post the question was my observation of really negative values in a GEO dataset (GSE3446) which should only be normalized with dCHip without additional transformation. I never, and I must say I rarely used dChip for normalization ... still I never observed negative values in pure dChip normalization. And this dataset has a range from -11000 up to 17000. So that is where I just lost, or still don't have, the slightest feeling for what the dataset range tells me. 
It is not z-score normalized. The sd's are unequal 1. Probably something similar. But then, would you say: 

"No judgement possible anymore about "present/absent"-states because the normal states are already curated by some mean value?"

Best regards,

Benjamin



-----Ursprüngliche Nachricht-----
Von: seandavi at gmail.com [mailto:seandavi at gmail.com] Im Auftrag von Sean Davis
Gesendet: Thursday, September 04, 2008 2:34 PM
An: Benjamin Otto
Cc: bioconductor at stat.math.ethz.ch
Betreff: Re: [BioC] PCR Validation threshold in dChip normalized data

On Thu, Sep 4, 2008 at 8:01 AM, Benjamin Otto <b.otto at uke.uni-hamburg.de> wrote:
> Hi,
>
> Given a dataset for Affymetrix arrays normalized with mas5 or rma we usually
> made the experience that signals below 80 (6,3 in log2 format) are hard to
> validate with PCR.
>
> Can somebody tell me, how I can judge on dChip normalized data in a analog
> way? Where can I draw a threshold to tell, which signal has good chances to
> withstand a verification with with PCR or even on protein level? And which
> signals usually indicate a much to low expression level?

I don't think this is an answerable question, exactly.  See Rafael
Irizarry's work on gene expression barcoding.

http://www.ncbi.nlm.nih.gov/pubmed/17906632

In short, each probeset has a different threshold for expression,
potentially.  Also, keep in mind that PCR, while held out as a "gold
standard" is not without its own biases.  Finally, for proteins, all
bets are off, as there are a number of highly relevant mechanisms for
regulation of protein expression that occur after transcription.

Not really an answer, but it is reality, I think.

Sean



-- 
Pflichtangaben gemäß Gesetz über elektronische Handelsregister und Genossenschaftsregister sowie das Unternehmensregister (EHUG):

Universitätsklinikum Hamburg-Eppendorf
Körperschaft des öffentlichen Rechts
Gerichtsstand: Hamburg

Vorstandsmitglieder:
Prof. Dr. Jörg F. Debatin (Vorsitzender)
Dr. Alexander Kirstein
Ricarda Klein
Prof. Dr. Dr. Uwe Koch-Gromus