[BioC] Filtering Codes (analysing Agilent 8x60k using limma)

[Gordon K Smyth]

Dear Muralidharan V,

See the case study in the limma User's Guide called "Section 11.8. Agilent 
Single-Channel Data: Gene expression in thymus from female Wistar rats". 
The description on GEO says that this is 8x60k data.

As far as I know, there is no difference in the analysis steps for 4x44k 
or 8x60k arrays.

Best wishes
Gordon

> Date: Fri, 27 Apr 2012 17:43:52 +0530
> From: Muralidharan V <muralidharanv89 at gmail.com>
> To: bioconductor at r-project.org
> Subject: [BioC] Filtering Codes
>
> Hai,
>
> I am using  the data obtained from Agilent 8x60k chip for the analysis of
> mRNA expression.  I have gone through lots of papers that describes only
> about  Agi 4x44 chips.
>
> Here am facing a trouble of filtering the genes using the LIMMA package in
> R+Bioconductor. What is the basic code implemented in doing this filtering
> process?
>
> I just want to know how the unwanted ProbeID,s or genes, which are of
> not importance, can be filtered out using the LIMMA package.
>
> The code for normalization  that i am using is:
>
> *y <- normalizeBetweenArrays(y, method="quantile")*
> *
> *
> *
> *
> Could you please help  me by providing the code that can be used for the
> filtering of 8x60k data using LIMMA package in R+Bioconductor?
>

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