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

[Sean Davis]

On Wed, Jan 20, 2010 at 12:12 AM, neeraj rana <kushrn at gmail.com> wrote:
> hi thanx sean,
>          In RG list after background correction i shall get the R and G with
> background corrected valves.I want to use subtract method to subtract the
> background intensities from the forground intensities.And then i want to
> remove the spots from the RG List which are not well above the background
> intensities.

Sounds like a plan.  Let us know if you have questions.

Sean

>
> On Tue, Jan 19, 2010 at 3:52 PM, Sean Davis <seandavi at gmail.com> wrote:
>>
>> 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.
>> >
>> >        [[alternative HTML version deleted]]
>> >
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>
>