[BioC] dataset dim for siggenes

ferreirafm at usp.br ferreirafm at usp.br
Fri Sep 12 21:53:49 CEST 2014

Hi Jim, 
Could you please possibly tell me which tests should I have to perform in order to ensure that my data fulfills the linear model assumptions? 
Turning back to my question "performing several different tests to decide which mirs to take", could you explain a little bit more why such approach doesn make sense. 

----- Mensagem original -----

> De: "James W. MacDonald" <jmacdon at uw.edu>
> Para: ferreirafm at usp.br
> Cc: "bioconductor" <bioconductor at r-project.org>
> Enviadas: Sexta-feira, 12 de Setembro de 2014 12:47:55
> Assunto: Re: [BioC] dataset dim for siggenes

> Hi Fred,

> I am assuming you have 116 miRNAs, and 60 samples. In which case you
> could probably just use a conventional t-test or linear model,
> although using limma wouldn't be a controversial decision. Not too
> sure about siggenes though. You have to estimate the proportion of
> true nulls, and I don't know if 116 comparisons are enough.

> But the larger question is the issue of running further statistical
> tests for validation. I am not sure what you mean by that.
> Quantitative PCR is (for better or worse) assumed to be the 'gold
> standard' for quantification of nucleic acid sequences, so there
> doesn't seem to be much more to do. Certainly re-running the
> analyses using a slightly different method isn't useful. That's like
> weighing yourself on a bunch of different scales; it tells you way
> more about the scales than it does about your weight.

> I think the next step (or really, the first step if you haven't
> already done so) is to ensure that your data meet all the underlying
> assumptions for linear modelling, so that you can have confidence in
> the conclusions you draw from the results.

> Best,

> Jim

> On Fri, Sep 12, 2014 at 11:18 AM, < ferreirafm at usp.br > wrote:

> > Hi list,
> > I have a qPCR 116 x60 data set processed with limma. Results showed
> > 30 DE miRNAs. My idea is to pick-up 10 of them for validation
> > running further statistical tests and taking the most recurrent
> > mirs
> > from all analyses (does it make sense?). Well, I was thinking of
> > using siggenes, however, their authors recommend it for high-
> > dimensional data. Will siggenes be suitable for my data? if not,
> > could someone suggest others packages and perhaps tests more
> > appropriated to this size data?
> > Best.
> > Fred
> > [[alternative HTML version deleted]]

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> --

> James W. MacDonald, M.S.
> Biostatistician
> University of Washington
> Environmental and Occupational Health Sciences
> 4225 Roosevelt Way NE, # 100
> Seattle WA 98105-6099

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