[BioC] DESEQ ANODEV : A time course study

Gordon K Smyth smyth at wehi.EDU.AU
Tue Jun 11 02:44:34 CEST 2013

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):


Best wishes

> 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

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