[BioC] Colourful way of visualising differential analysis results

Yannick Wurm yannick.wurm at unil.ch
Mon Nov 10 17:54:55 CET 2008

Hi Dan,

for this kind of thing, I'll fit another limma model just to obtain  
estimates of what needs to be visualized...
In one case, I needed to separately visualize expression levels from  
each biological replicate, but variability was such that I had  
grouped them together in my model. To estimate expression levels for  
each biological replicate, I recreated a targets file, separating  
each biological replicate by name. Then calculated a fit, and asked  
for contrasts between each sample and one RNA which I chose as  
reference.  (centering expression levels within each gene afterwards  
works too)

Despite a complex design it was thus possible to generate a heatmap  
where each of the 8 biological replicated RNAs from 3 different  
conditions where represented separately.

hope this helps,


          yannick . wurm @ unil . ch
Ant Genomics, Ecology & Evolution @ Lausanne

On Nov 10, 2008, at 17:33 , Daniel Brewer wrote:

> Dear all,
> I am doing some work on a two-colour microarray (Agilent)  
> experiment and
> I have used limma to do some differential analysis.  The person I am
> doing this work was keen to have a heatmap of the differentially
> expressed genes expression levels.  Unfortunately, the design is  
> rather
> complex and random (closer to a loop design than a common  
> reference) so
> its not possible to produce a traditional heatmap.  I was wondering if
> anyone had any suggestions of a colourful way to show that the
> expression of the two groups are different?
> In particular I was thinking that there must be estimates of the
> expression and error in each group by the linear model, but couldn't
> work out how to find these.
> Thanks
> Dan
> -- 
> **************************************************************
> Daniel Brewer, Ph.D.
> Institute of Cancer Research
> Molecular Carcinogenesis
> Email: daniel.brewer at icr.ac.uk
> **************************************************************
> The Institute of Cancer Research: Royal Cancer Hospital, a  
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