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.
- Version0.1.2
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- Last release09/06/2021
Documentation
Team
Vidal Fey
Henri Sara
Show author detailsRolesAuthor
Insights
Last 30 days
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Depends2 packages
- Imports6 packages
- Suggests2 packages