Question: Which Method Is The Best Dissimilarity Measurement For Hierarchical Clustering Of Dna Methylation Data
gravatar for Gangcai
8.9 years ago by
Berlin Or Shanghai
Gangcai230 wrote:

Dear all, I have performed hierarchical clustering for bisulfite DNA methylation data using two different dissimilarity methods: euclidean distance and pearson correlation by using R package pvclust. However,the tree structure based on those two methods are different. My question is which one should I use for hierarchical clustering of bimodal distributed DNA methylation data? Is there any published paper that have already compared different dissimilarity methods?

Thanks in advance.

methylation clustering dna • 3.5k views
ADD COMMENTlink modified 3 months ago by Biostar ♦♦ 20 • written 8.9 years ago by Gangcai230

As said often before (here and elsewhere) the attempt to recommend a single best method for data-mining is futile, given the lack of a gold standard to compare your results with. Clustering is exploratory and used for hypothesis generation, therefore the way to go is to apply many different methods (including other clustering methods: kmeans, Mclust) and try to evaluate the results in the light of your biological knowledge. Also, use e.g. GO analysis, pathway analysis and GSEA).

ADD REPLYlink written 8.9 years ago by Michael Dondrup47k
gravatar for Sean Davis
8.9 years ago by
Sean Davis26k
National Institutes of Health, Bethesda, MD
Sean Davis26k wrote:

I'd suggest converting these values to M-values, compute the distance metric, then display the beta values. Keep in mind that there is no "right" answer when clustering, so experimentation is necessary.

ADD COMMENTlink written 8.9 years ago by Sean Davis26k
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