scellpam: Applying Partitioning Around Medoids to Single Cell Data with High Number of Cells

PAM (Partitioning Around Medoids) algorithm application to samples of single cell sequencing techniques with a high number of cells (as many as the computer memory allows). The package uses a binary format to store matrices (either full, sparse or symmetric) in files written in the disk that can contain any data type (not just double) which allows its manipulation when memory is sufficient to load them as int or float, but not as double. The PAM implementation is done in parallel, using several/all the cores of the machine, if it has them. This package shares a great part of its code with packages 'jmatrix' and 'parallelpam' but their functionality is included here so there is no need to install them.

Version: 1.4.4
Imports: Rcpp (≥ 1.0.8), memuse (≥ 4.2.1), cluster (≥ 2.1.4)
LinkingTo: Rcpp
Suggests: rmarkdown, knitr, DuoClustering2018, scater, splatter
Published: 2023-06-24
Author: Juan Domingo ORCID iD [aut, cre], Guillermo Ayala ORCID iD [ctb], Spanish Ministry of Science and Innovation, MCIN/AEI <doi:10.13039/501100011033> [fnd]
Maintainer: Juan Domingo <Juan.Domingo at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: NEWS
CRAN checks: scellpam results


Reference manual: scellpam.pdf
Vignettes: jmatrixsc


Package source: scellpam_1.4.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): scellpam_1.4.4.tgz, r-oldrel (arm64): scellpam_1.4.4.tgz, r-release (x86_64): scellpam_1.4.4.tgz, r-oldrel (x86_64): scellpam_1.4.4.tgz
Old sources: scellpam archive


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