I would appreciate if someone with extensive knowledge of Model-based clustering specifically on gene expression data, can give a fair comparison on classification potential, Dos and Don't, between available algorithm such as
1.parsimonious Gaussian mixture model (EPGMM) family ,
2. nonparametric model-based clustering, and
3. Gaussian mixture model
All three approaches are implemented in R package; pgmm, pdfCluster, and Mclus, respectively.
Ref.
1 Article Model-Based Clustering of Microarray Expression Data via Lat...
2. Article A novel approach to the clustering of microarray data via no...
3. https://www.stat.washington.edu/mclust/
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