[BioC] duplicate genes in Affy arrays

Suresh Gopalan gopalans at comcast.net
Fri Aug 19 04:23:28 CEST 2005


I don't know if there is a consensus on this issue yet.  When I did dealt 
with this to do some categorial over representation analysis, I used the 3' 
most probeset (www.pnas.org/cgi/doi/10.1073/pnas.0501211102).  There are 
pitfalls to this approach also, though biologically sound. The other 
approach I have seen implemented in one software is to use the probeset with 
highest expression.

As to the last question, it depends.  Based on published articles using 
whole genome tiling arrays and listening to the current interpretation, the 
answer could be tricky.


Suresh Gopalan, Ph.D.

----- Original Message ----- 
From: <jsv at stat.ohio-state.edu>
To: <bioconductor at stat.math.ethz.ch>
Sent: Thursday, August 18, 2005 7:50 AM
Subject: [BioC] duplicate genes in Affy arrays

> Is there any general procedure for handling duplicate genes in Affy 
> arrays?
> For example, for the hu6800 array which has 7129 probe sets,
> there are 869 genes that are represented by more than one probe set,
> with one gene (ACTB) being represented by 9 probe sets.
> g.symbols=aafSymbol(X.gnames,"hu6800")
> ug.symbols <- unlist(g.symbols)
> length(ug.symbols) #6980 (7129-6980 = 149 with no symbols)
> symbol.usage <- table(ug.symbols)
> sum(symbol.usage>1)  # 869
> max(symbol.usage)  #9
> Ignoring this would seem to invalidate a number of multiple comparison
> procedures.  Is it reasonable to average probe set expression levels for
> the same gene?  Are there any "pre-processing" routines that address this
> issue?
> The flip side of this question is "Do probe sets with the same gene symbol
> really specify the same gene? Does it matter which annotational method is
> used to name genes?"
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