[BioC] RMA + loess normalisation and filtering

[Naomi Altman]

This topic keeps coming up.  Any references supported by data that show 
some method is preferable?

Wolfgang, how many replicates do you think are needed for your method to be 
reasonable?

(I've gotten burned by reviewers on this one.)

--Naomi

At 12:01 PM 4/19/2005, Wolfgang Huber wrote:

>Hi again,
>
>
>>>question 1: I have performed *RMA normalisation *of my Affymetrix data. 
>>>However, for further analysis I think it is necessary to *filter* the 
>>>data (non-expressed genes or below background). However I don't know the 
>>>best way to filter the genes that are not expressed or very low 
>>>expressed (below the background), based on the RMA normalisation data.
>>
>>My preference is to select genes based on their overall variability, 
>>using a criterions such as
>>    z = apply(exprs(x), 1, IQR)
>
>
>
>Just remembered - a discussion (with data) on whether to select on mean 
>level or variability can be found here:
>
>http://www.bepress.com/bioconductor/paper7/
>
>There are also additional ideas on pre-filtering, in order to alleviate 
>the loss of power from multiple testing.
>
>--
>Best regards
>   Wolfgang
>
>-------------------------------------
>Wolfgang Huber
>European Bioinformatics Institute
>European Molecular Biology Laboratory
>Cambridge CB10 1SD
>England
>Phone: +44 1223 494642
>Fax:   +44 1223 494486
>Http:  www.ebi.ac.uk/huber
>
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Naomi S. Altman                                814-865-3791 (voice)
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Bioinformatics Consulting Center
Dept. of Statistics                              814-863-7114 (fax)
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