[BioC] Large # of significant genes with SAM

[Charles C. Berry]

Vincent,

As others have pointed out, this could be the actual state of nature or 
could be artifacts that you can straighten out by a closer look at the 
data.

I have found this approach to be helpul:

 	Bradley Efron. Large Scale Simultaneous Hypothesis Testing: The
 	Choice of a Null Hypothesis. JASA, 99(465):96104, Mar 2004

As is pointed out there, artifacts in the data may tend to inflate test 
statistics 'across the board' leading to very large numbers of supposedly 
significant (or truly discovered) genes.

The suggested approach (recalibrating the null variance and shifting the 
location) compensates for this even when you cannot specifically identify 
the artifacts.

It is a fairly simple exercise in R to implement this. I can send you some 
hints, if you wish

Chuck


On Mon, 9 May 2005, Vincent Detours wrote:

> Dear all,
>
> Your expert opinion are most welcome on the following.
>
> I am finding using siggenes' SAM @ q<0.05 (26 samples on cDNA chips)
> that 37% of all genes are regulated with respect to patient-matched
> "normal" tissues in somme tumors not particularly known for huge
> aneuploidy. Looking at another data set from the same cancer but
> collected by another group on indepentent samples on Affy, I got 34%.
> The number seems to hold.
>
> How to interpret this? Are really 30% of the genes disturbed, even to
> a small extent, in these tumors? Could SAM do something wrong? If yes,
> how to verify it?
>
> Any advise, shared experience, references, etc. are welcome
>
> Cheers
>
> Vincent
>
>
> ------------------------------------------
> Vincent Detours, Ph.D.
> IRIBHM
> Bldg C, room C.4.116
> ULB, Campus Erasme, CP602
> 808 route de Lennik
> B-1070 Brussels
> Belgium
>
> Phone: +32-2-555 4220
> Fax: +32-2-555 4655
>
> E-mail: vdetours at ulb.ac.be
>
> URL: http://homepages.ulb.ac.be/~vdetours/
>
>
>

Charles C. Berry                        (858) 534-2098
                                          Dept of Family/Preventive Medicine
E mailto:cberry at tajo.ucsd.edu	         UC San Diego
http://biostat.ucsd.edu/~cberry/         La Jolla, San Diego 92093-0717