[BioC] read.ilmn() and variation between chips

[Gordon K Smyth]

On Tue, 2 Jul 2013, Rao,Xiayu wrote:

> Dr. Smyth,
>
> Thanks a lot for your important message! I did read your limma user 
> guide, and only found that "If there are multiple probe summary profiles 
> to be read, and the samples are summarized in a targets frame, then the 
> read.ilmn.targets function can be used." When I typed ?read.ilmn.targets 
> in R, not much syntax showing up. I also read your paper: Optimizing the 
> noise versus bias trade-off for Illumina Whole Genome Expression 
> BeadChips. Nucleic Acids Research 38, e204. But I did not find an 
> example for that. Could you please let me know how read.ilmn() reads 
> multiple files and collate them.

Thanks for explaining the documentation you have read, but I had thought 
the natural place to start would be the help page for read.ilmn(), which 
you can access by ?read.ilmn.  This tells you that 'files' can be a vector 
of file names.

Best wishes
Gordon

> For a beginner in microarray data analysis, it is so great to have your 
> help!!! Really appreciate it!
>
> Thanks,
> Xiayu
>
>
> -----Original Message-----
> From: Gordon K Smyth [mailto:smyth at wehi.EDU.AU]
> Sent: Friday, June 28, 2013 6:46 PM
> To: Rao,Xiayu
> Cc: Bioconductor mailing list
> Subject: RE: read.ilmn() and variation between chips
>
> Dear Xiayu,
>
> Genome Studio normally exports multiple BeadChips to the same probe 
> summary profile file.  Our core centre normally exports all the chips 
> for each experiment to the same file.  Even if you do have multiple 
> files, read.ilmn() will read multiple files and collate them for you.
>
> Have you read the documentation?
>
> Best wishes
> Gordon
>
> On Fri, 28 Jun 2013, Rao,Xiayu wrote:
>
>> Hello, Gordon
>>
>> Thanks a lot for answering my two questions. The information you
>> provided was very important to us.
>>
>> One quick question, you said that read.ilmn() reads the files as
>> output by Genome Studio without any need for intermediate processing.
>> What if I have so many samples from several chips, and I read in the
>> data from each chip using read.ilmn(), and then I want to do
>> comparisons based on all the samples? How to combine them?
>>
>> Really appreciate your kind help!
>>
>> Thanks,
>> Xiayu
>>
>>
>>
>> -----Original Message-----
>> From: Gordon K Smyth [mailto:smyth at wehi.EDU.AU]
>> Sent: Friday, June 28, 2013 2:37 AM
>> To: Rao,Xiayu
>> Cc: Bioconductor mailing list
>> Subject: read.ilmn() and variation between chips
>>
>> Dear Xiayu,
>>
>> Yes, it is good enough.  neqc() has done between-array normalization already, and there is no need for within-array normalization for Illumina BeadChips.
>>
>> Please look at the help page
>>
>>   ?neqc
>>
>> The read stages that you describe sound complicated.  read.ilmn() reads the files as output by Genome Studio at our core facility without any need for intermediate processing.
>>
>> Best wishes
>> Gordon
>>
>> -------------------- original message -------------------- [BioC]
>> read.ilmn() and variation between chips Rao,Xiayu XRao at
>> mdanderson.org Wed Jun 26 20:08:09 CEST 2013
>>
>> Hello,
>>
>> I have a question about background correction and normalization. Please 
>> help me out! Thank you for your time!
>>
>> I have four chips of microarray experiments, and therefore four data 
>> sets.
>> I combined them together by merging on ProbeID and read in them as one 
>> file using read.ilmn(), and I combined all the control probe files into 
>> one and read it in. I just followed the limma user guide and use neqc() 
>> for background correction and normalization. Is it good enough? Do I 
>> need to consider within array and between array normalization?
>>
>> Thanks,
>> Xiayu

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