[BioC] Illumina array analysis

[Wei Shi]

The neqc() function in limma performs a normexp background correction (aided by control probes) and quantile normalization for the BeadChip data. For a comparison between neqc and vst used in lumi package, have a look at this paper:

http://www.ncbi.nlm.nih.gov/pubmed?term=PMID%3A%2020929874

Cheers,
Wei

On Oct 18, 2011, at 11:33 PM, Belmont, John W wrote:

> Consider using the lumi package for normalization and data QC. Lumi implements the variance stabilization and robust spline normalization procedure that takes advantage of the multiple bead data produced by Illumina arrays.
> 
> -----Original Message-----
> From: bioconductor-bounces at r-project.org [mailto:bioconductor-bounces at r-project.org] On Behalf Of Wei Shi
> Sent: Monday, October 17, 2011 9:11 PM
> To: Chintanu
> Cc: bioc
> Subject: Re: [BioC] Illumina array analysis
> 
> Hi Chintanu,
> 
> There is a case study for analyzing Illumina BeadChip data in limma user's guide. Type the following command in your R to bring up limma user's guide and then have a look at section 11.7.
> 
> limmaUsersGuide()
> 
> 
> Cheers,
> Wei
> 
> On Oct 18, 2011, at 12:55 PM, Chintanu wrote:
> 
>> Hi,
>> 
>> I'm new to my exploration with analysing illumina microarray data using r.
>> While looking for some example case study (so that I can do my analysis
>> taking pointers from that/those examples), I am unable to find anything
>> useful. I would appreciate if you could either provide me with some pointers
>> in that direction or share your codes that you have done while doing your
>> illumina analysis.
>> 
>> I am mainly interested in the following: (i) read in the illumina files &
>> check the quality of the files, (iii) normalization (any type), (iii)
>> applying Limma and pick the differentially expressed genes.
>> 
>> Thank you.
>> 
>> regards,
>> Chintanu
>> 
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>> 
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