[BioC] #how to filter bad spots from two color agilent array,

[Sean Davis]

On Mon, Jan 18, 2010 at 11:26 PM, neeraj rana <kushrn at gmail.com> wrote:
> hi,
>
>     I am working on two color 4x44Agilent array.I normalized the data with
> Bioconductor,I used the following scripts to normalize the data.i want to
> filterout the spots which are not good to be analysis across the array.how
> can i filter the spots which are having the negative value after background
> substraction.I want to do this befor normalization.
>
>>limma(library)
>> library(limma)
>> targets_nod=readTargets("Both_negatv_postv_nods.txt")
>> targets_nod
>   SampleNumber                                          FileName    Cy3
> Cy5
> 1             1                        135kt_251485025987_1_4.txt normal
> tumor
> 2             2                        157kt_251485025985_1_3.txt normal
> tumor
> 3             3                        159kt_251485025985_1_4.txt normal
> tumor
> 4             4                        171kt_251485026134_1_3.txt normal
> tumor
> 5             5                        179kt_251485026134_1_4.txt normal
> tumor
> 6             6                         28kt_251485025987_1_1.txt normal
> tumor
> 7             7                         58kt_251485025986_1_1.txt normal
> tumor
>> RG<-read.maimages(targets_nod$FileName, source="agilent")

Hi, Neeraj.

RG is an RGList object and can be subset just like a normal data.frame
or matrix (samples are columns, genes are rows).  RG$G contains the
Green intensities while RG$R contains the Red intensities.

Sean

>> RG<-backgroundCorrect (RG,method="none")
>> MA<-normalizeWithinArrays(RG, method="loess")
>> MA <- normalizeBetweenArrays(RG, method="quantile")
>
> thank you,
> Neeraj Rana
> IISC Banglore,INDIA.
>
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