[BioC] DESEQ ANODEV : A time course study

[Ryan C. Thompson]

Hi Michael,

The simplest and most understandable approach I've found is to define a 
single factor that splits your data into all the groups. So there would 
be levels for disease-T0, disease-T1, disease-t3, control-T0, 
control-T1, and control-T3. Then you can use ~0+group as your model 
formula and define whatever contrasts you desire between these six groups.

-Ryan Thompson

On Mon 17 Jun 2013 10:54:59 AM PDT, Michael Breen wrote:
>
> Gordon!
>
> On second pass, edgeR doesn't seem to address my question.
>
> We have disease and control data spread over 3 time points (baseline-T0,
> time after disease causing event-T1, elapsed time after event-T3) for each
> of these two conditions. I want to be able to find DEGs accordingly to
> condition across time-points to decipher which times (either at treatment
> or elapsed time after treatment) our genes are DE.
>
> Any further insight would be fantastic.
>
> Yours,
>
> Michael
>
>
>
> -----Original Message-----
> From: "Michael Breen" <mbreen at vapop.ucsd.edu>
> To: "Gordon K Smyth" <smyth at wehi.EDU.AU>
> Cc: Bioconductor mailing list <bioconductor at r-project.org>
> Date: Mon, 10 Jun 2013 20:47:10 -0700
> Subject: Re: [BioC] DESEQ ANODEV : A time course study
>
> Cheers!
>
> I think this is applicable to our needs.
>
> Thank you Gentlemen!
>
>
> -----Original Message-----
>
> From: Gordon K Smyth <smyth at wehi.EDU.AU>
>
> To: Michael Breen <mbreen at vapop.ucsd.edu>
>
> Cc: Bioconductor mailing list <bioconductor at r-project.org>
>
> Date: Tue, 11 Jun 2013 10:44:34 +1000 (AUS Eastern Standard Time)
>
> Subject: DESEQ ANODEV : A time course study
>
>
>
>
> Dear Michael,
>
>
>
> What you want to do is easy and fast using the edgeR package, without any
>
> need for ad hoc workarounds like subsetting your data. See McCarthy et
>
> all (NAR 2012):
>
>
>
> http://www.ncbi.nlm.nih.gov/pubmed/22287627
> [ http://www.ncbi.nlm.nih.gov/pubmed/22287627]
>
>
>
> Best wishes
>
> Gordon
>
>
>
>
>
>>
>> Date: Mon, 10 Jun 2013 08:41:49 +0200
>
>
>>
>> From: Simon Anders <anders at embl.de>
>
>
>>
>> To: bioconductor at r-project.org
>
>
>>
>> Subject: Re: [BioC] DESEQ ANODEV : A time course study
>
>
>>
>>
>
>
>>
>> Hi Michael
>
>
>>
>>
>
>
>>
>> On 08/06/13 03:00, Michael Breen wrote:
>
>
>
>
>>
>>>
>>> What we aim to do is to test for DE of transcripts across all 3 time
>>
>
>
>>
>>>
>>> points for disease and controls seperatly (using DESeq ANODEV) but we
>>
>
>
>>
>>>
>>> want to be able to identify at which time points these transcripts are
>>
>
>
>>
>>>
>>> being DE. In other words, we want to compare DE transcripts with
>>
>
>
>>
>>>
>>> respect to specific time points between cases and controls. Our
>>
>
>
>>
>>>
>>> remaining code looks like this:
>>
>
>
>>
>>>
>>>
>>
>
>
>>
>>>
>>> fit0 <- fitNbinomGLMs (cds, count ~ timecourse)
>>
>
>
>>
>>>
>>> fit1 <- fitNbinomGLMs ( cds, count ~ timecourse + condition )
>>
>
>
>>
>>>
>>> str(fit1)
>>
>
>
>>
>>
>
>
>>
>> One possibility would be to subset your data to only samples from one
>
>
>>
>> time point and then test cases against control to see the genes that are
>
>
>>
>> DE at this time point, then go on to the next one. If you consider this
>
>
>>
>> a post-hoc test and only look at the genes which show overall
>
>
>>
>> sensitivity, you can probably be more lenient on the significance
>
>
>>
>> threshold. Maybe other people on the list have input on this point.
>
>
>>
>>
>
>
>>
>> Simon
>
>
>
>
> ______________________________
> ________________________________________
>
> The information in this email is confidential and intend...{{dropped:11}}
>
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>
>
>
>
>
> On Tue, Jun 11, 2013 at 11:32 AM, Michael Breen 
> <mbreen at vapop.ucsd.edu>wrote:
>
>>
>>
>>
>>
>> -----Original Message-----
>> From: Gordon K Smyth <smyth at wehi.EDU.AU>
>> To: Michael Breen <mbreen at vapop.ucsd.edu>
>> Cc: Bioconductor mailing list <bioconductor at r-project.org>
>> Date: Tue, 11 Jun 2013 10:44:34 +1000 (AUS Eastern Standard Time)
>> Subject: DESEQ ANODEV : A time course study
>>
>> Dear Michael,
>>
>> What you want to do is easy and fast using the edgeR package, without any
>> need for ad hoc workarounds like subsetting your data. See McCarthy et
>> all (NAR 2012):
>>
>> http://www.ncbi.nlm.nih.gov/pubmed/22287627
>>
>> Best wishes
>> Gordon
>>
>>
>>>
>>> Date: Mon, 10 Jun 2013 08:41:49 +0200
>>> From: Simon Anders <anders at embl.de>
>>> To: bioconductor at r-project.org
>>> Subject: Re: [BioC] DESEQ ANODEV : A time course study
>>>
>>> Hi Michael
>>>
>>> On 08/06/13 03:00, Michael Breen wrote:
>>
>>
>>>
>>>>
>>>> What we aim to do is to test for DE of transcripts across all 3 time
>>>> points for disease and controls seperatly (using DESeq ANODEV) but we
>>>> want to be able to identify at which time points these transcripts are
>>>> being DE. In other words, we want to compare DE transcripts with
>>>> respect to specific time points between cases and controls. Our
>>>> remaining code looks like this:
>>>>
>>>> fit0 <- fitNbinomGLMs (cds, count ~ timecourse)
>>>> fit1 <- fitNbinomGLMs ( cds, count ~ timecourse + condition )
>>>> str(fit1)
>>>
>>>
>>> One possibility would be to subset your data to only samples from one
>>> time point and then test cases against control to see the genes that are
>>> DE at this time point, then go on to the next one. If you consider this
>>> a post-hoc test and only look at the genes which show overall
>>> sensitivity, you can probably be more lenient on the significance
>>> threshold. Maybe other people on the list have input on this point.
>>>
>>> Simon
>>
>>
>> ______________________________________________________________________
>> The information in this email is confidential and intended solely for the
>> addressee.
>> You must not disclose, forward, print or use it without the permission of
>> the sender.
>> ______________________________________________________________________
>>
>>
>
>
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>
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