[BioC] DESeq2 : when the variable of interest is not a factor

[Peterson, Leif]

Try looking at independent component analysis, which is like PCA of qualitative data.  However, multivariate methods for MDS type methods and many other scales (nominal, continuous, etc) were developed quite deeply by Jan Deleeuw and colleagues many years ago.  A software package called LISREL for structural equation modeling (sem) is yet another approach which may have been expanded to cover hidden constructs for categorical factors.
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On Sep 11, 2013, at 6:32 AM, "Jose M Garcia Manteiga" <garciamanteiga.josemanuel at hsr.it> wrote:

>> 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
> 
> 
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> 
> 
> 
> 
> ------------------------------------------------------------
> 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 at 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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