[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.
--Naomi
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.
>
>cheers,
>Mark
>-----------------------------------------------------
>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
>>Agi4x44PreProcess
>>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
>>normalizeWithinArrays
>>and marray's maNormMain only do that for two color arrays. I haven't
>>find
>>any function for normalizing single channel arrays, except for
>>affymetrix chips.
>>
>>Thanks
>>
>>P-L Poulin
>>Research assistant
>>Université Laval
>>www.arborea.ca
>>
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>
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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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