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PAMhm  

Generate Heatmaps Based on Partitioning Around Medoids (PAM)
View on CRAN: Click here


Download and install PAMhm package within the R console
Install from CRAN:
install.packages("PAMhm")

Install from Github:
library("remotes")
install_github("cran/PAMhm")

Install by package version:
library("remotes")
install_version("PAMhm", "0.1.2")



Attach the package and use:
library("PAMhm")
Maintained by
Vidal Fey
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-09-06
Latest Update: 2021-09-06
Description:
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) . 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.
How to cite:
Vidal Fey (2021). PAMhm: Generate Heatmaps Based on Partitioning Around Medoids (PAM). R package version 0.1.2, https://cran.r-project.org/web/packages/PAMhm. Accessed 02 Feb. 2025.
Previous versions and publish date:
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Other R packages that PAMhm depends, imports, suggests or enhances
Complete documentation for PAMhm
Functions, R codes and Examples using the PAMhm R package
Some associated functions: PAM.hm . PAMhm . 
Some associated R codes: PAM.hm.R . centerMatrix.R . clustNum.R . doPAMhm.R . makeClustList.R . makeXlsList.R . make_heatmap.R . make_res_folder.R . plot.PAM.R . plotAdjust.R . readPAM.R . setCol.R . setDendro.R .  Full PAMhm package functions and examples
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