[BioC] Microarray data analysis for experiments using amplified RNA

Robert Gentleman rgentlem at fhcrc.org
Wed Feb 9 16:17:12 CET 2005


One of the problems with amplified mRNA is that not all mRNA species  
are going to get amplified at the same rate (and probably for some the  
rate is zero), also, as I understand it the resulting mRNAs will tend  
not to be full length. So this affects the binding, and hence the  
estimated expression levels (and I do not believe it matters what  
platform you are using; there will most likely be some peculiarities).  
So, that basically means that you want all samples to have been  
amplified using the same method, and in some sense the same amount.  
Otherwise, you are not really comparing like with like. The RNA  
degredation plots can be quite helpful in this regard - as they can  
help to pinpoint arrays that might be substantially different.

  Robert




On Feb 9, 2005, at 5:36 AM, Swati Ranade wrote:

> Hi,
> I have done some experiments using amplified RNA (Rayan Baugh's method  
> which
> I modified slightly) probes with affy chips. The study design is a  
> simple
> comparison of knockout mutant vs wild type. My question was: Is it ok  
> to use
> the same statistical algorithms one would apply for standard microarray
> experiments or do I need to follow a different strategy? Can anybody  
> give
> pointers?
>
> Thanks,
>
> Swati
>
> Swati Ranade
> Bauer Center for Genomics Research
> 7 Divinity Av
> Cambridge
> MA 02138
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/bioconductor
>
>
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| Robert Gentleman              phone: (206) 667-7700                    
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| Head, Program in Computational Biology   fax:  (206) 667-1319   |
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