[BioC] dealing with negative values in illumina

[Mete Civelek]

Hi,

I have used both Lumi and limma to normalize the data using vst followed by
rns (Lumi) and negqc (limma). Is there a function in either of the package
that allows me to output the processed data at the "gene" level as opposed
to "probe" level? I wrote my own script to look for the probes that annotate
to the same gene and average them but I was wondering if there is already a
built-in function in either of the packages.

Thanks

Mete Civelek

-----Original Message-----
From: bioconductor-bounces at r-project.org
[mailto:bioconductor-bounces at r-project.org] On Behalf Of Wei Shi
Sent: Thursday, March 24, 2011 2:43 PM
To: Pan Du
Cc: bioconductor at r-project.org; Prasad Siddavatam
Subject: Re: [BioC] dealing with negative values in illumina

If BeadStudio output is available, there won't be a need to process negative
values.

It does not make sense to me to log transform a data set which has already
been normalized.

For a comparison between different BeadChip preprocessing algorithms, please
see http://www.ncbi.nlm.nih.gov/pubmed/20929874


On Mar 24, 2011, at 11:44 PM, Pan Du wrote:

> 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 at wehi.EDU.AU>
> To: Prasad Siddavatam <siddavatam at gmail.com>
> Cc: bioconductor at stat.math.ethz.ch
> Subject: Re: [BioC] dealing with negative values in illumina
> Message-ID: <11617AF1-F976-43EF-9560-F4D283A96CB5 at 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
>>
>
>       [[alternative HTML version deleted]]
>
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