[BioC] One-color spotted microarrays analysis

Naomi Altman naomi at stat.psu.edu
Fri May 22 05:18:43 CEST 2009

I am aware of 2 methods.

You could do quantile normalization.  This is 
very stringent as it forces the overall 
expression distribution to be the same on every array.

You could pick one array (or the genewise mean or 
median of all arrays) to act as the "control" and 
lowess normalize everything relative to that array.


At 09:05 PM 5/21/2009, Mark Cowley wrote:
>Hi Pier-Luc,
>What sort of within array normalisation are you trying to perform? ie
>what issues have you spotted in your data that you think need removing?
>There are no print-tip's as such on an agilent array since they're
>printed by fancy ink jet printers.
>You can't do lowess, unless you make a 'virtual' 2nd channel, perhaps
>by taking the average of all channels.
>Mark Cowley, PhD
>Peter Wills Bioinformatics Centre
>Garvan Institute of Medical Research, Sydney, Australia
>On 22/05/2009, at 12:47 AM, Pier-Luc Poulin wrote:
>>Hi Massimo and everyone,
>>Thanks for the suggestion. I've read documentation about
>>and Affy packages but I still need advice. Agi4x44PreProcess
>>contains no
>>method for normalization between print tips within arrays.
>>Our data consists of single color spotted chips. We need to find a way
>>in bioconductor to do within array normalization. Limma's
>>and marray's maNormMain only do that for two color arrays. I haven't
>>any function for normalizing single channel arrays, except for
>>affymetrix chips.
>>P-L Poulin
>>Research assistant
>>Université Laval
>>Bioconductor mailing list
>>Bioconductor at stat.math.ethz.ch
>>Search the archives: 
>Bioconductor mailing list
>Bioconductor at stat.math.ethz.ch
>Search the archives: 

Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
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