[BioC] limma power question

Fangxin Hong fhong at salk.edu
Fri Nov 5 19:13:32 CET 2004

Although some genes have significant differences, it is not necesssarily
for limma to identify them out. In other words, genes that are not
identified by limma may be significant. It all depends on the power of
your test, which may in turn decided by your sample size, your error
varaince (noise scale) and the test you choose. Sometimes, some
significant differences might be small for your data to identify them out.

Since you have done the experiment, you can't change sample size and error
variance, maybe you can try other method or low down the overall
sifnificance you controlled.

Hopefully this helps.

> Hi,
> I am using limma to analyse an experiment where I am comparing the
> response in stimulated verses un-stimulated cells in individuals with
> and without disease.
> When I ask how individuals with or without disease respond
> differently to the stimulus there are no significant genes when the p
> values are adjusted.
> I know that there are differences which have been confirmed by
> qRT-PCR ( and can be demonstarted by analysing data using fold change
> only) and these genes have the highest ranked p values in the limma
> analysis (although not significant when adjusted).
> I have tried to filter the data set (to the 3000 most variable genes)
> so there are less comparisons being made and the differences are
> still not significant.
> I am using hgu133plus2 chips with 3 replicates.
> regards
> Anthony
> --
> ______________________________________________
> Anthony Bosco - PhD Student
> Institute for Child Health Research
> (Company Limited by Guarantee ACN 009 278 755)
> Subiaco, Western Australia, 6008
> Ph 61 8 9489  , Fax 61 8 9489 7700
> email anthonyb at ichr.uwa.edu.au
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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

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