[BioC] Limma Coefficients using lmscFit

Gordon K Smyth smyth at wehi.EDU.AU
Thu Dec 22 08:27:27 CET 2005

> 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.

Best wishes

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