[BioC] Subject: Re: Normalization of arrays where most of the genes change

Alicia Oshlack oshlack at wehi.EDU.AU
Thu May 14 13:34:43 CEST 2009

Hi Yiwen,

In cases where you know the subset of genes that are not changin you can
use limma as outlined in:



        <C2A9EB528D6C3D44AD457C54AD0C7CD545A85C49 at NIHMLBX01.nih.gov>


Thanks for getting back to me so quickly! I took a look at the VSN
package and
some threads in the mailing archive, it looks like the right tool to
try. However,
I am just wondering, if there are people fitting LOESS on a subset of
genes and any comment on that.

Thanks in advance!


From: Davis, Sean (NCI)
Sent: Wednesday, May 13, 2009 9:01 AM
To: He, Yiwen (NIH/CIT) [C]
Cc: bioconductor at stat.math.ethz.ch
Subject: Re: [BioC] Normalization of arrays where most of the genes change

On Wed, May 13, 2009 at 8:54 AM, He, Yiwen (NIH/CIT) [C]
<heyiwen at mail.nih.gov<mailto:heyiwen at mail.nih.gov>> wrote:

We have some arrays where most of the genes are turned on under certain
conditions. This violates the assumption that most normalization methods
What would be the best way to handle such arrays? We are using Agilent
arrays but
as I understand the platform should not matter. I'm wondering, if LOESS
or Quntile
normalization can be used on a (small) subset of invariable genes and
expand to
the whole array? If so, is there such a tool in BioC?

Thank you very much!

Hi, Yiwen.  There has been some discussion on the list before (you might
check the
archives), but vsn might be a reasonable place to start.


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