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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 |
| 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.
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