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 > > ______________________________________________________________________ > The information in this email is confidential and inte...{{dropped:6}}