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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.
Version: | 0.1.2 |
Depends: | heatmapFlex, cluster, grDevices, graphics, stats |
Imports: | RColorBrewer, R.utils, readxl, readmoRe, utils, plyr, robustHD |
Suggests: | rmarkdown, knitr |
Published: | 2021-09-06 |
DOI: | 10.32614/CRAN.package.PAMhm |
Author: | Vidal Fey [aut, cre], Henri Sara [aut] |
Maintainer: | Vidal Fey <vidal.fey at gmail.com> |
License: | GPL-3 |
NeedsCompilation: | no |
CRAN checks: | PAMhm results |
Reference manual: | PAMhm.pdf |
Vignettes: |
Generate Heatmaps Based on Partitioning Around Medoids (PAM) |
Package source: | PAMhm_0.1.2.tar.gz |
Windows binaries: | r-devel: PAMhm_0.1.2.zip, r-release: PAMhm_0.1.2.zip, r-oldrel: PAMhm_0.1.2.zip |
macOS binaries: | r-release (arm64): PAMhm_0.1.2.tgz, r-oldrel (arm64): PAMhm_0.1.2.tgz, r-release (x86_64): PAMhm_0.1.2.tgz, r-oldrel (x86_64): PAMhm_0.1.2.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.