[BioC] Limma:short question

[James MacDonald]

Julia,

In my opinion, you should always log transform microarray data before
fitting a linear model. Microarray data is usually highly right skewed,
and taking logs helps to make the data distribution more symmetrical. In
addition, taking logs tends to make the variance independent of the
intensity (of course, vsn does a better job than a simple log
transform). This will get you much closer to fulfilling the assumptions
underlying the linear model and t-tests you are going to perform.

Best,

Jim



James W. MacDonald
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623

>>> Julia Engelmann <julia.engelmann at biozentrum.uni-wuerzburg.de>
01/27/04 11:15AM >>>
Hi all,

I am using limma on Affymetrix data and want to fit a linear model
with

fit <- lm.series(exprs(E), design)

My question is:
Is the data in E supposed to be on a log scale (like after using vsn)
or not?

Thanks for your help,
Julia

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