[BioC] Which package for gene expression correlation analysis

[Wolfgang Huber]

Dear Yuan

you probably want to cluster the genes, e.g. using hierarchical 
clustering and heatmap display or k-means clustering. The "heatmap.2" 
function in the gplots package might be a good place to start, as is the 
book http://www.bioconductor.org/pub/biocases or a Google search on the 
terms "heatmap" and "microarray".

It is important to think about what choice of distance metric between 
genes you want, and/or to try different ones.

        Best wishes
           Wolfgang


On Jun/28/10 4:53 PM, Yuan Hao wrote:
> Dear List,
>
> I would like to ask if there is such a bioconductor package available that
> can help to achieve the following purpose. Thank you very much in advance!
>
> I got 16 Affy chips corresponding to 4 samples: wild-type treated,
> wide-type untreated, knocked-down treated, and knocked-down untreated,
> i.e. 4 replicates for each sample.
>
> I want to look at the expression correlations between genes. Say, my gene
> of interest is gene X. I would like to find out other genes on the chip
> which have the similar expression profiles with gene X across samples. In
> other words, if expression levels of gene X increased from wild-type
> treated to knocked-out treated, I would like to find all the other genes
> have the same trend.
>
> Any comments would be appreciated!
>
> The best,
> Yuan
>
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-- 


Wolfgang Huber
EMBL
http://www.embl.de/research/units/genome_biology/huber