[BioC] Interspecies differential expression of orthologs with Edger

[assaf www]

Dear Gordon

I am aware of the limitations of the corss-species inference -
Still , it is critical for me to minimize false positives, before the
real-time PCR validation stage.

Just trying to understand some other things, that may, or may not, be
related to the corss-species issue:
Edger manual says that any kind of "genomic feature" may be used,
but can "genomic feature" also be defined as 'groups of genes' ?
I mean, can it be correct to try Edger after summing up the counts of genes
belonging to specific categories
(e.g. gene families) ? so instead of having 12,000 genes I end up with, say
2,000 gene groups ?
this can also be good for the FDR, etc.

Thanks a lot, all the Best,
Assaf

On Sun, Sep 7, 2014 at 4:11 AM, Gordon K Smyth <smyth at wehi.edu.au> wrote:

> Dear Assaf,
>
> You are getting the sort of results that I would expect you to get when
> you try to compare two RNA sources that are very different.
>
> The diagonal lines in the MA plot are simply a result of having low counts
> (0,1,2 etc) in one species and high counts in the other for the same genes.
>
> When you compare different species, I'd intuitively expect almost every
> gene to be differentially expressed to some degree.  So I'm not surprised
> that a large proportion of genes are assesssed as DE.
>
> That's about as much help as I can give you.  I can't give advice that
> would allow you to get the same sort of results as you might be used to,
> because comparing different species isn't a normal thing to do.
>
> Best wishes
> Gordon
>
>
>  Date: Fri, 5 Sep 2014 23:22:28 +0300
>> From: assaf www <assafwww at gmail.com>
>> To: Gordon K Smyth <smyth at wehi.edu.au>
>> Cc: Bioconductor mailing list <bioconductor at r-project.org>
>> Subject: Re: [BioC] Interspecies differential expression of orthologs
>>         with    Edger
>>
>> Thanks Gordon,
>>
>> To summarize the results I got on the cross-species data, after embedding
>> the length-effect to the GLM offset matrix, as in the code you sent,
>> please
>> see the attached MA plot:
>>
>> 1) for >5 and <-5 log fold change, genes' logFC is positively correlated
>> with mean log CPM, something I haven?t seen before in Edger standard runs.
>> 2) most genes with fold change around > 1.3, or < -1.3, are significant,
>> which looks to me too ?liberal?. Please note that each group contains 6
>> true biological replicates (variance within each group is large) .
>>
>> The first problem worries me most, any idea is very welcomed.
>>
>> Many thanks,
>> Assaf
>>
>>
>>
>> On Wed, Sep 3, 2014 at 2:08 AM, Gordon K Smyth <smyth at wehi.edu.au> wrote:
>>
>>
>>> On Tue, 2 Sep 2014, assaf www wrote:
>>>
>>>  Does Edger DE analysis is built on the assumption that most genes are
>>> not
>>>
>>>> differentially expressed, and that only a small portion of them do (say
>>>> <20%)  ?
>>>>
>>>>
>>> Only the calcNormFactors() step of edgeR makes any assumption of this
>>> sort. calcNormFactors assumes that either that most genes are not DE or
>>> that the DE is reasonably symmetric.
>>>
>>>  I mean, in cross-species studies, or when comparing different tissues of
>>>
>>>> the same organism, if this assumption doesn't hold, should it be a
>>>> serious
>>>> concern ?
>>>>
>>>>
>>> In a cross-species comparison there will be many DE genes, but some will
>>> be up and some will be down.  The DE will not be all in one direction, I
>>> would guess that normalization will not be a serious concern.
>>>
>>> Of all the concerns with cross-species comparisons, this seems to me to
>>> be
>>> far from the most serious.
>>>
>>> Best wishes
>>> Gordon
>>>
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