Hi Prasad

If you only have processed Illumina GEO data and the maximum of expression
value is larger than 100, then I guess the negative values were caused by
background correction.  Also most negative values should be close to zero,
or else the data may have some problem.  If you don't want to throw away
those negative values, you can do log2(x+offset) to force the negative
values as positives. This may affect the genes with low expression values.
If you have BeadStudio output file, then you can use vst transformation in
lumi package instead of log transform. The vst  transformation can handle
negative values.


Pan

Date: Thu, 24 Mar 2011 09:21:56 +1100
From: Wei Shi <shi@wehi.EDU.AU>
To: Prasad Siddavatam <siddavatam@gmail.com>
Cc: bioconductor@stat.math.ethz.ch
Subject: Re: [BioC] dealing with negative values in illumina
Message-ID: <11617AF1-F976-43EF-9560-F4D283A96CB5@wehi.edu.au>
Content-Type: text/plain; charset="us-ascii"

Dear Prasad:

       I am not quite sure what your question is. But if you want to
normalize the raw data by yourself and you want use the control probes for
the normalization, then you might try limma neqc function which can infer
the intensities of negative control probes using regular probe intensities
and their detection p values. The neqc function will then perform a normexp
background correction aided by negative controls followed by quantile
normalization and log2 transformation.

       Hope this helps.

Cheers,
Wei


On Mar 23, 2011, at 4:28 PM, Prasad Siddavatam wrote:

> Dear List,
>
> I am reprocessing a previously processed dataset from NCBI GEO. This is a
> Illumina microarray chip. The data provided at GEO is either normalized
with
> negative probe values or unnormalized data without control spot
information.
>
> If I avoid the probes with the negative values (can't transfer to logs)
that
> leaves only 9500 out of 22000 probes?
>
> Can anybody please suggest how to approach this problem?
>
> Appreciate your help
>
> Prasad
>

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