> Dear all,
> I take advantage to add another question to statisticians, since many times I have had the same question in mind, for microarray but also for RNA-Seq. How about a PLS (partial least square - projection of latent variables) kind of multivariate regression to find groups of variables (Latent variables) which correlate to a continuous variable? Is there any caveat in using it with reads-count table? There are some papers out there that try to use PLS, and its "factor" version PLS-DA to select variables with transcriptomics data but I would like to know people in the field's opinions on that.
> thanks in advance
> Regards
> 
> Jose
> ------------------------------------------------------------
> Jose M. Garcia Manteiga PhD
> 
> Data analyst in Functional Genomics
> Center for Translational Genomics and Bioinformatics
> DIBIT2-A3 Room 21
> San Raffaele Scientific Institute
> Via Olgettina 58
> 20132 Milano
> Italy
> 
> Office: +39 02 26439114







------------------------------------------------------------
Jose M. Garcia Manteiga PhD

Data analyst in Functional Genomics
Center for Translational Genomics and Bioinformatics
DIBIT2-A3 Room 21
San Raffaele Scientific Institute
Via Olgettina 58
20132 Milano
Italy

Office: +39 02 26439114






> 
> On Sep 11, 2013, at 11:45 AM, Marie Sémon <marie.semon@ens-lyon.fr> wrote:
> 
>> Dear all,
>> 
>> I wish to find genes whose expression profile correlates with a variable
>> of interest, which is quantitative (say, the weight of the individuals).
>> Is it possible/a good practice to use DESeq2 for this?
>> 
>> One one hand the vignette clearly describes factors (qualitative) 
>> variables, but, on the other hand there is this sentence, p8:
>> "If the variable of interest is not a factor, the log2 fold change can 
>> be interpreted as the amount of doubling observed on average for every 
>> unit of change."
>> 
>> Many thanks for you help
>> 
>> With kind regards,
>> 
>> Marie
>> 
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> 


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