Generate Heatmaps Based on Partitioning Around Medoids (PAM) R package PAMhm version 0.1.2 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. Software Depends: heatmapFlex, cluster, grDevices, graphics, stats Imports: RColorBrewer, R.utils, readxl, readmoRe, utils, plyr, robustHD Suggests: rmarkdown, knitr Vidal Fey <vidal.fey@gmail.com> Comprehensive R Archive Network (CRAN) Vidal Fey [aut, cre], Henri Sara [aut] GPL-3 2021-09-06 application/tgz https://CRAN.R-project.org/package=PAMhm doi:10.32614/CRAN.package.PAMhm