[BioC] GC-RMA - interpretation of the expression levels

Uri David Akavia uridavid at netvision.net.il
Fri Jun 10 15:43:13 CEST 2005

Pintilie, Melania wrote:

> Hello everyone,
> I am a statistician at the Ontario Cancer Institute. Recently, I had to
> analyse an affymetrix dataset. The data have been normalized and the level
> expressions were calculated using GC RMA as implemented in R.
> My role is to analyse the expression levels (which were calculated using GC
> RMA) using SAM and other statistical techniques.
> The expression levels which were given to me (calculated with GC RMA) are
> very large: all are >1. I wonder if this is what one would expect. The
> analyst assures me that a log transformation was also applied.
> I am not sure how to interpret this numbers. What would be the levels of:
> 'not expressed', 'over expressed', or 'under expressed'?

A recommendation I've recieved from statisticans in my University 
(Tel-Aviv University in Israel) is to use MAS Absent/Present marks as a 
filtering guide, if possible.
Remove all those genes who were marked Absent or Marginal.

More information about the Bioconductor mailing list