[BioC] Limma Coefficients using lmscFit

[Naomi Altman]

Dear Sean,

lmscFit does not use the spot weights.

--Naomi

At 06:57 AM 12/22/2005, Sean Davis wrote:



>On 12/22/05 2:27 AM, "Gordon K Smyth" <smyth at wehi.EDU.AU> wrote:
>
> >> Date: Tue, 20 Dec 2005 21:12:24 -0500
> >> From: Naomi Altman <naomi at stat.psu.edu>
> >> Subject: [BioC] Limma Coefficients using lmscFit
> >> To: bioconductor at stat.math.ethz.ch
> >> Cc: QING ZHANG <qxz5 at psu.edu>
> >>
> >> Being a big believer in single-channel analysis of loop designs, I
> >> used lmscFit to analyze my loop design data. All went well until the
> >> investigator requested the normalized single channel data.
> >> Since lmscFit actually operates on M and A, we took the same MAlist,
> >> and created R and G using RG.MA.
> >>
> >> To check the computation, we then computed the treatment means by
> >> hand for a few genes.  These did not work out to the same treatment
> >> means obtained from lmscFit (using model ~-1+Trt).
> >>
> >> I hope that someone can explain why these are not equal.  (And I
> >> really hope that this is not another case where I did not read the
> >> documentation sufficiently carefully.)
> >>
> >>
> >>
> >> Naomi S. Altman                                814-865-3791 (voice)
> >> Associate Professor
> >> Dept. of Statistics                              814-863-7114 (fax)
> >> Penn State University                         814-865-1348 (Statistics)
> >> University Park, PA 16802-2111
> >
> > I assume you're taking means of log-intensities.  lmscFit() uses 
> generalised
> > least squares with
> > block weights (as for a mixed model analysis), so the values from
> > lmscFit()$coef will be simple
> > means only for balanced designs.  The coefficients should not in 
> a different
> > ball park to the
> > means however.
>
>Spot weights could also make the simple means different from the estimates,
>even for balanced designs, couldn't they?
>
>Sean
>
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Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111