ulrb: Unsupervised Learning Based Definition of Microbial Rare Biosphere

A tool to define rare biosphere. 'ulrb' solves the problem of the definition of rarity by replacing arbitrary thresholds with an unsupervised machine learning algorithm (partitioning around medoids, or k-medoids). This algorithm works for any type of microbiome data, provided there is a species abundance table. For validation of this method to different species abundance tables see Pascoal et al, 2024 (in peer-review). This method also works for non-microbiome data.

Version: 0.1.5
Depends: R (≥ 2.10)
Imports: cluster, dplyr, ggplot2, purrr, rlang, stats, tidyr, clusterSim, gridExtra
Suggests: knitr, rmarkdown, stringr, testthat (≥ 3.0.0), vegan
Published: 2024-06-18
DOI: 10.32614/CRAN.package.ulrb
Author: Francisco Pascoal ORCID iD [aut, cre], Paula Branco ORCID iD [aut], Luís Torgo ORCID iD [aut], Rodrigo Costa ORCID iD [aut], Catarina Magalhães ORCID iD [aut]
Maintainer: Francisco Pascoal <fpascoal1996 at gmail.com>
BugReports: https://github.com/pascoalf/ulrb/issues
License: GPL (≥ 3)
URL: https://pascoalf.github.io/ulrb/
NeedsCompilation: no
Citation: ulrb citation info
Materials: README
CRAN checks: ulrb results


Reference manual: ulrb.pdf
Vignettes: Glossary
Integration of ulrb in a simple microbial ecology workflow
Alternative classifications with ulrb
Tutorial to define rare biosphere with ulrb


Package source: ulrb_0.1.5.tar.gz
Windows binaries: r-devel: ulrb_0.1.5.zip, r-release: ulrb_0.1.5.zip, r-oldrel: ulrb_0.1.5.zip
macOS binaries: r-release (arm64): ulrb_0.1.5.tgz, r-oldrel (arm64): ulrb_0.1.3.tgz, r-release (x86_64): ulrb_0.1.5.tgz, r-oldrel (x86_64): ulrb_0.1.3.tgz
Old sources: ulrb archive


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