[BioC] Data analysis
jps at sanger.ac.uk
Mon Oct 13 18:20:24 MEST 2003
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.
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.
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
(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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