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

[Rao,Xiayu]

Dr. Shi,

Thank you very much for your detailed explanation! It is very helpful to me. The limma package your research group developed really help us out to analyze microarray data and other data.

Thanks again!

Best regards,
Xiayu


-----Original Message-----
From: Wei Shi [mailto:shi at wehi.EDU.AU] 
Sent: Tuesday, July 02, 2013 6:23 PM
To: Rao,Xiayu
Cc: 'Gordon K Smyth'; Bioconductor mailing list
Subject: Re: [BioC] read.ilmn() and variation between chips

Dear Xiayu,

If you have saved your file into to a tab delimited target file like below

files	ctrlfiles	other_columns
probe_profile_file1.txt	control_probe_profile_file1.txt	...
probe_profile_file2.txt	control_probe_profile_file2.txt	...
...

Let's call this file "Targets.txt", then you can use the following command to read in the data:

> library(limma)
> targets <- readTargets()
> data <- read.ilmn.targets(targets)

Alternatively, you can use read.ilmn to read in your data if you do not have a target file:

> data <- 
> read.ilmn(files=c("probe_profile_file1.txt","probe_profile_file2.txt")
> , 
> ctrlfiles=c("control_probe_profile_file1.txt","control_probe_profile_f
> ile2.txt"))

Note that your files should be generated from the same version of GenomeStudio/BeadStudio, otherwise you may run into problems.

Hope this helps.

Cheers,
Wei

On Jul 3, 2013, at 2:29 AM, 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. 
> 
> 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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