[BioC] goodness-of-fit for limma

fhong at salk.edu fhong at salk.edu
Tue Jun 7 20:54:05 CEST 2005

Hi, Bin

> I'm doing some affy microarray analysis using limma, and I'm not a
> statistician.  I was told that I need to check if the model fits the data
> before get the significant gene lists. So how should I do it in limma? And
> is it really necessary? If not, why?

>From a statistical viewpoint, only when the model ( for example, linear
model used in limma) is a good analogy of the true data generating
mechanism, the results ( like differential genes found) are valid. The
common check is residual plots, to see whether the residual ( difference
between the true value and fitted value) satisfy the assumption. You would
extract residuals from lmFit.
However, I don't see many people doing this when identifying genes. If you
worry about that linear model might not explain the data well, you can go
to some other non-parametric methods, like RankProd and siggenes.

Hopu this will help


> Thanks a lot!
> Bin
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Fangxin Hong  Ph.D.
Plant Biology Laboratory
The Salk Institute
10010 N. Torrey Pines Rd.
La Jolla, CA 92037
E-mail: fhong at salk.edu
(Phone): 858-453-4100 ext 1105

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