[BioC] DNA micro-array normalization

[michael watson (IAH-C)]

This is definitely processed data, and without access to the original data or a description of the analysis methodology, your options are limited.

Personally, I'd do a test for normality on the "Signal" values, and if they turn out to be normal, I'd run a simple t-test (control vs treatment) on each gene and correct the p-values for multiple testing.

Simple stuff, but it should work.
________________________________________
From: bioconductor-bounces at stat.math.ethz.ch [bioconductor-bounces at stat.math.ethz.ch] On Behalf Of avehna [avhena at gmail.com]
Sent: 16 February 2010 19:47
To: bioconductor at stat.math.ethz.ch
Subject: [BioC] DNA micro-array normalization

Hi There,

I've got a DNA microarray dataset that looks like this:

*    Probe                 Signal          Detection
Detection_p-value                   Descriptions*
AFFX-BioB-5_at       181                P
0.00011                  "E. coli  GEN=bioB  DB_XREF=gb:J04423.1"
AFFX-BioB-M_at     227.3              P                 0.000044
   "E. coli  GEN=bioB  DB_XREF=gb:J04423.1"
AFFX-BioC-5_at     499.2               P
0.000052                "E. coli  GEN=bioC  DB_XREF=gb:J04423.1"

I have control and treatment with 3 replicas for each one of them.

But I'm not sure whether these data have been already normalized, and on the
other hand, this is not the typical affymetrix format...

Could you help me in this regard? What is the typical signal range for rough
affymetrix data? (these data range from 0 to 9000)

If the data have been already normalized, Can I calculate the mean (for
treatment and control) followed by the differential expression of genes
without taking into account the "Detection" column?

(I guess I will need to build my ExpressionSet from scratch)

Thanks a lot (I'm a newbie in bioconductor and micro-array analysis). I will
appreciate you help!

Avhena

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