heyi xiao | 16 Aug 21:33 2013
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Re: RNA degradation plot with oligo package GeneFeatureSet objects

Hi Jim,
Thanks for the informative notes. I really learned things about RNA degradation and affy array design!
I see you what mean. But I only use RNA degradation as a quality assessment tool. I am less interested in
estimate exactly how much RNA degradation happened in the RNA molecules in one sample/array, I am more
interested in the different degradation patterns seen across different samples. Normally degradation
curves for different samples stack together consistently and nicely. Even with the newer generation
Affy arrays, an outlier degradation curve always suggest some quality issue, mostly likely RNA
degradation. Such RNA degradation curves together with other quality check help me either kick out the
problematic samples or have them redone.
BTW, currently only oligo package seems to work with the new Ovine Gene 1.1 ST array, for which I don’t see
an CDF package in bioconductor as other affy chip types. Therefore, I can’t go with affy and other
packages which provide RNA degradation plots. Can I use makecdfenv package to build CDF package from PGF
and CLF files?
Heyi

--------------------------------------------
On Fri, 8/16/13, James W. MacDonald <jmacdon <at> uw.edu> wrote:

 Subject: Re: [BioC] RNA degradation plot with oligo package GeneFeatureSet objects

 Cc: bioconductor <at> r-project.org
 Date: Friday, August 16, 2013, 12:52 PM

 Hi Heyi,

 On 8/14/2013 4:47 PM, heyi xiao wrote:
 > Hi all,
 > In affy package, I can use AffyRNAdeg and
 plotAffyRNAdeg to plot and check RNA degradation. Is there
 any way to do so in oligo package for GeneFeatureSet,which
 is equivalent to AffyBatch in affy package. I look at the
 GeneFeatureSet and AffyBatch, they quite similar. But not
 sure what can be done here. I can either modify AffyRNAdeg
 and plotAffyRNAdeg functions to fit them for GeneFeatureSet,
 or I can convert GeneFeatureSet to AffyBatch and use the
 affy package degradation functions. Any suggestions would be
 highly appreciated.

 While I suppose you could hypothetically do the conversion,
 I wonder if it makes conceptual sense.

 The 3'-biased Affy arrays were all based off an oligo-dT
 primer that was used to convert mRNA to cDNA, so the reverse
 transcription proceeded from the 3' end of the mRNA, always.
 In this case you can wonder about two things. First, how far
 did the RT step proceed? Did you in general get good RT all
 the way to the most 5' of the probes in the probesets?

 Second, since we were using the polyA tail at the 3' end, by
 definition the mRNA wasn't degraded from the 3' end.
 However, it might have had more or less extensive
 degradation from the 5' end, so the RT may have gone to
 completion, but the degradation had proceeded past the most
 5' probes.

 So both things are confounded, as we cannot distinguish RT
 that didn't proceed too far from highly degraded mRNA, but
 no matter. What we could do is say how much signal we were
 getting from the more 5' probes, and decide if we wanted to
 do something about that (like only use the first 8 probes or
 whatever).

 For the newer generation of Affy arrays, we use a random
 primer, so the RT step proceeds from a random point in the
 transcript and proceeds towards the 5' end (at least I think
 it is still directional). Since the RT no longer starts from
 one end of the transcript, it is no longer clear what
 differential amounts of probe signal would actually
 signify.

 In addition, with the newer generation of Affy arrays, we
 can collapse the probes into different probesets, depending
 on what we are trying to measure (e.g., you can try to
 measure expression at the exon level or the transcript
 level).

 I think trying to do this would be more difficult than it
 would be worth, especially given that I don't know what you
 would do if you were to decide there had been degradation.

 Best,

 Jim

 > Heyi
 > 
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 -- James W. MacDonald, M.S.
 Biostatistician
 University of Washington
 Environmental and Occupational Health Sciences
 4225 Roosevelt Way NE, # 100
 Seattle WA 98105-6099

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