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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

Documentation:

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

Downloads:

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_0.1.5.tgz, r-release (x86_64): ulrb_0.1.5.tgz, r-oldrel (x86_64): ulrb_0.1.5.tgz
Old sources: ulrb archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ulrb to link to this page.

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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