[BioC] Data analysis

Gordon Smyth smyth at wehi.edu.au
Tue Oct 14 12:11:19 MEST 2003

At 02:20 AM 14/10/2003, Jason Skelton wrote:
>I have a question about data analysis after normalisation
>I have normalised in limma and applied the generalized least squares 
>linear models to my data with very nice results!
>My experiment is a Three sample experiment
>(Three different treatments)compared to a commmon reference.
>The Three samples have six slides per experiment, 3 in one dye orientation 
>and 3 dye swapped to give 18 slides in total.
>I have approx 3500 genes in duplicate on my array at present.
>Currently I have normalised all three sets of data seperately but would 
>like to be able to compare the three data sets.
>I was thinking of using the mva functions like dist/hclust etc.
>My questions:
>Is this the best way of comparing this data or are there other/better 
>methods that could be used that anyone has had experience with.

I would use the limma commands lmFit (or lm.series or gls.series) followed 
by makeContrasts, eBayes and classifyTests. See the earliers posts:


This would allow you to answer the following questions:

1. Which genes are differentially expressed between each pair of treatments?
2. Which genes are differentially expressed between each treatment and the 
3. Which genes show _any_ differences between the treatments?

Your problem doesn't sound like a cluster analysis problem to me.


>e.g. similar to the two-sample experiment example in limma user guide
>where results from the  linear model and ebayes are displayed with a heatmap ?
>(sorry I'm presuming that this is the kind of thing I should be doing ?)
>Also I'm presuming the data I want to use for these methods are the 
>normalised $M values ? OR do I want to use the results from 
>gls.series/lm.series and ebayes for a 3 sample comparison ?
>please could someone give me an example of the best method they recommend 
>with some commands that I could try using...
>Thanks very much to anyone who can help

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