[BioC] [Bioc] RNAseq less sensitive than microarrays? Is it a statistical issue?

[Ryan C. Thompson]

Hi Thomas,

Gordon Smyth has noted previously on this list that limma's voom method 
is happy to accept raw counts, CPM, FPKM, and base counts (read counts 
times read length, allows splitting reads across exons). My 
understanding is that voom doesn't depend or exploit the discrete nature 
of count data that is fed to it, and can handle any data for which it 
can properly model the mean-variance relationship (heteroskedasticity). 
I'm sure Gordon could elaborate on this if I've missed anything.

Also, note that "mean coverage" is more or less just another way to 
spell FPKM. And even if you want to calculate some other expression 
measure such as FPKM, you still need to properly assign reads to genes 
or transcripts, so using an alternate expression measure doesn't get 
around the difficulties associated with read counting, unless I'm 
missing something.

-Ryan Thompson

On Tue May 21 08:49:43 2013, Thomas Girke wrote:
>
> Hi Simon,
>
> Because of these complications, I am sometimes wondering whether one
> couldn't use for many RNA-Seq use cases coverage values (e.g. mean
> coverage) as raw expression measure instead of read counts. Has anyone
> systematically tested whether this would be a suitable approach for the
> downstream DEG analysis? Right now everyone believes RNA-Seq analysis
> requires read counting, but honestly I don't see why that is. Perhaps
> the benefits of this are so minor that it is not worth dealing with a
> different type of expression measure.
>
> Thomas
>
> On Mon, May 20, 2013 at 11:15:04PM +0000, Simon Anders wrote:
>>
>> Dear Lucia and list
>>
>> On second reading, I noticed that my previous post sounded quite
>> aggressive, which was not my intention. Sorry. I shouldn't write e-mails
>> that late at night.
>>
>> Anyway: We had a lot of discussion on this list and others recently
>> about how to correctly obtain a count table for differential expression
>> analysis from aligned RNA-Seq reads. From these discussions, it has
>> become clear that this is a task with many more pitfalls than one might
>> expect at first. In microarray analysis, there is no need to do this,
>> and so read counting is a likely culprit when such discrepancies are
>> noted. This is why exact details on the procedure are so important.
>>
>> Simon
>>
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>
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