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PAMhm: Generate Heatmaps Based on Partitioning Around Medoids (PAM)
Data are partitioned (clustered) into k clusters "around medoids", which is a more robust version of K-means implemented in the function pam() in the 'cluster' package. The PAM algorithm is described in Kaufman and Rousseeuw (1990) <doi:10.1002/9780470316801>. Please refer to the pam() function documentation for more references. Clustered data is plotted as a split heatmap allowing visualisation of representative "group-clusters" (medoids) in the data as separated fractions of the graph while those "sub-clusters" are visualised as a traditional heatmap based on hierarchical clustering.
Getting started
Browse package contents
Package details |
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| Author | Vidal Fey [aut, cre], Henri Sara [aut] |
| Maintainer | Vidal Fey <vidal.fey@gmail.com> |
| License | GPL-3 |
| Version | 0.1.2 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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