[BioC] unnormalised vs normalised distribution

Michal Okoniewski MOkoniewski at PICR.man.ac.uk
Fri Jun 9 15:13:17 CEST 2006


And what do you get when you use standard RMA instead of GCRMA?
I have run GCRMA on my data and see similar pattern - the second peak 
is small, but is there. In general GCRMA seems to result in much more 
small values - RMA has a bit "nicer" distribution. 

Once I've run a distribution of correlation of all probesets against
For MAS and RMA I got what I expected - almost normal distribution, 
slightly shifted towards positive r. For GCRMA the distribution 
had not really normal shape (almost symmetric convex function with the
maximum roughly in the same place as RMA - close to 0). From that time
on, I believe that GCRMA may impose some artifacts onto data...


-----Original Message-----
From: bioconductor-bounces at stat.math.ethz.ch
[mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of botto
Sent: 08 June 2006 13:24
To: bioconductor at stat.math.ethz.ch
Subject: [BioC] unnormalised vs normalised distribution

Dear list members,

I've been looking at the distribution plots of pm intensities and the
corresponding expression values calculated by gcrma for a certain data
set. Now I'm wondering what the best interpretation of these plots would
be, because the former looks quite usual while the latter seems quite
"unfamiliar" to me (nearly like a bimodal distribution, a jpg file
should be attached). The data measured is simply the expression for
certain mouse tumor tissues. Can anybody explain why after the
background correction and normalisation I get this distribution shape?

log(PM) density:

|      *
|    *  *
|   *    *
|  *     *
|  *      *
| *        *
|*          *
|             ***********

gcrma-expression values:

|      *
|    *  *
|   *    *
|  *     *
|  *      *
| *        *     * * *
|*          ****       *
|                        ***

Benjamin Otto
Universitaetsklinikum Eppendorf Hamburg
Institut fuer Klinische Chemie
Martinistrasse 52
20246 Hamburg

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