[BioC] replicates and low expression levels

Rafael A. Irizarry ririzarr at jhsph.edu
Fri May 30 14:42:45 MEST 2003


if you look at an MA plot of expression values obtained from MAS 5.0 on
two replicate arrays you will see that for genes with low expression you 
get very large fold changes. when using MAS 5.0, if you dont filter genes 
with observed low intensity you will get lots of false positives (some 
call this the fish tail effect). however, by filtering genes 
in such a way you run the risk of creating various false negatives.

if you use, for example, dChip or RMA this fish tail problem is not nearly 
as bad. if you normalize with vsn it pretty much goes away completely. 
thus, using  
RMA, or dChip, and/or vsn, etc...,   
the P/A  calls are not essential for avoiding many false positives.
some of this is discussed here:
http://nar.oupjournals.org/cgi/content/full/31/4/e15?ijkey=EAz2cYYbEWQrE&keytype=ref&siteid=nar 


hope this helps,
rafael


On Fri, 30 May 2003, Crispin Miller 
wrote:

> Hi,
> Just a quick question about low expression levels on Affy systems - I hope it's not too off-topic; it is about normalisation and data analysis...
> I've heard a lot of people advocating that it's a good idea to perform an initial filtering on either Present Marginal or Absent calls, or on gene-expression levels (so that only genes with an expression > 40, say, after scaling to a TGT of 100 using the MAS5.0 algorithm, are part of the further analysis). Firstly, am I right in thinking that this is to eliminate data that are too close to the background noise level of the system.
> 
> I wanted to canvas opinion as to whether people feel we need to do this if we have replicates and are using statistical tests - rather than just fold-changes - to identify 'interesting' genes. Does the statistical testing do this job for us?
> 
> Crispin
>  
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