[BioC] Normalize data across platforms

[Priscila Darakjian]

Maybe this will help you regarding control probes across platforms --> https://aberdeen.ac.uk/ims/facilities/microarray/documents/chipcontrols.doc
	
Regards

Priscila

-----Original Message-----
From: bioconductor-bounces at stat.math.ethz.ch [mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of Steve Taylor
Sent: Tuesday, March 31, 2009 7:46 AM
To: michael watson (IAH-C)
Cc: Bioconductor
Subject: Re: [BioC] Normalize data across platforms

Hi,

Thanks for your reply.

> 
> Quantile normalisation is a very conservative normalisation, and there are fears in some quarters that it may lead to over-normalisation.  However, as you're comparing between datasets, this may be what you're after.
> 

I agree. I am just looking for large differences so I am hoping it might be ok.

> Alternatively, have you considered using "housekeeping" or control genes?  These should be constant across arrays, experiments etc (if you believe in them) and so could provide a good normalisation factor.
> 

Does anyone know if affy has control probes that are consistent across platforms?

Kind regards and thanks,

Steve
------------------------------------------------------------------
Medical Sciences Division
Weatherall Institute of Molecular Medicine/Sir William Dunn School
Oxford University

_______________________________________________
Bioconductor mailing list
Bioconductor at stat.math.ethz.ch
https://stat.ethz.ch/mailman/listinfo/bioconductor
Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor