[BioC] Implications of design argument to limma::voom?

Ryan C. Thompson rct at thompsonclan.org
Wed Jun 5 01:28:18 CEST 2013


Thanks. That answers my question.

On Tue 04 Jun 2013 04:21:44 PM PDT, Gordon K Smyth wrote:
> Hi Ryan,
>
> The design matrix to voom must be the same as you use for lmFit (or be
> an alternative parametrization of the same model), otherwise voom is
> analysing the wrong variances.
>
> Best wishes
> Gordon
>
> ------------------ original message --------------------
> [BioC] Implications of design argument to limma::voom?
> Ryan C. Thompson rct at thompsonclan.org
> Wed Jun 5 01:03:27 CEST 2013
>
> Hi,
>
> I'm using limma's voom function to analyze some of my data, and I'm
> wondering about the implications of the design argument to voom. The
> default design is an intercept-only design, i.e. a model formula of ~1.
> However, I can also pass in the same experimental design that I will
> pass to lmFit later (or conceivably any other design). I'm not entirely
> sure what assumptions I'm making by choosing either of these options.
> Can someone familiar with such things explain what the implications of
> passing or not passing a design to voom are?
>
> Similarly, I have the same question for DESeq's
> varianceStabilizingTransformation: I can use estimateDispersions with or
> without a design matrix and then do the VST either way, and I'm not sure
> what assumptions I am making in either case.
>
> Thanks,
>
> -Ryan Thompson
>
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