[BioC] Limma question_Intra-Spot Correlation Question

[Gordon K Smyth]

Dear Judith,

Getting negative intensities has nothing to do with normalization, but 
everything to do with background correction.  Please see page 24 of the 
limma User's Guide:

"we often find

  RG <- backgroundCorrect(RG, method="normexp", offset=50)

to be preferable to the simple background subtraction when using output 
from most image analysis programs. This method adjusts the foreground 
adaptively for the background intensities and results in strictly positive 
adjusted intensities, i.e., negative or zero corrected intensities are 
avoided."

Best wishes
Gordon

> Message: 10
> Date: Sun, 05 Feb 2012 11:45:12 +0100
> From: jgomez at uni-potsdam.de
> To: Bioconductor mailing list <bioconductor at r-project.org>
> Subject: [BioC] Limma question_Intra-Spot Correlation Question
>
> Dear List,
> I have a set of Agilent chips that I would like to analyse following
> the procedure for separate channel analysis.
> I just want to add that following the brief procedure outline in Limma
> User Guide wasn't useful.
> I have made the targets file as usual
>  FileName   Cy3   Cy5
> 1 US83800208_252412610022_1_4.txt  WT_4  OX_4
> 2 US83800208_252412610019_1_1.txt  KD_4  WT_4
> 3 US83800208_252412610019_1_2.txt  OX_4  KD_4
> 4 US83800208_252412610019_1_3.txt OX_21  OX_4
> 5 US83800208_252412610019_1_4.txt WT_21  WT_4
> 6 US83800208_252412610020_1_1.txt  KD_4 KD_21
> 7 US83800208_252412610020_1_2.txt WT_21 OX_21
> 8 US83800208_252412610021_2_1.txt KD_21 WT_21
> 9 US83800208_252412610020_1_3.txt OX_21 KD_21
> I read the chips using read.maimages and creating an RG object along
> the way. Then I normalized the arrays using Aquantile (Normalization
> Between Arrays). I convert the targets file and then looks like this:
>  channel.col                        FileName Target
> 1.1           1 US83800208_252412610022_1_4.txt   WT_4
> 1.2           2 US83800208_252412610022_1_4.txt   OX_4
> 2.1           1 US83800208_252412610019_1_1.txt   KD_4
> 2.2           2 US83800208_252412610019_1_1.txt   WT_4
> 3.1           1 US83800208_252412610019_1_2.txt   OX_4
> 3.2           2 US83800208_252412610019_1_2.txt   KD_4
> 4.1           1 US83800208_252412610019_1_3.txt  OX_21
> 4.2           2 US83800208_252412610019_1_3.txt   OX_4
> 5.1           1 US83800208_252412610019_1_4.txt  WT_21
> 5.2           2 US83800208_252412610019_1_4.txt   WT_4
> 6.1           1 US83800208_252412610020_1_1.txt   KD_4
> 6.2           2 US83800208_252412610020_1_1.txt  KD_21
> 7.1           1 US83800208_252412610020_1_2.txt  WT_21
> 7.2           2 US83800208_252412610020_1_2.txt  OX_21
> 8.1           1 US83800208_252412610021_2_1.txt  KD_21
> 8.2           2 US83800208_252412610021_2_1.txt  WT_21
> 9.1           1 US83800208_252412610020_1_3.txt  OX_21
> 9.2           2 US83800208_252412610020_1_3.txt  KD_21
> When using the function intraspotCorrelation I got an error regarding
> " Missing or infinite values found in M or A".
> Checking older post regarding the erro, it may be becaouse few probes
> have after normalization negative intensities.
> I would like to know if the process I started is the right one for
> this kind of analysis and second If there is a kind of filter I can
> use in limma to get rid of those neg intensities to proceed to the
> next step.
> Thanks in advance for any help.
> Cheers,
> Judy
>
> -- 
> Judith Lucia Gomez, PhD
> Centre for Plant Biotechnology and Genomics - CBGP
> 28223 Pozuelo de Alarc?n (Madrid)
> Spain

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