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 [aut, cre], Paula Branco [aut], Luís Torgo [aut], Rodrigo Costa [aut], Catarina Magalhães [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_0.1.5.tgz, r-release (x86_64): ulrb_0.1.5.tgz, r-oldrel (x86_64): ulrb_0.1.5.tgz |
Old sources: | ulrb archive |
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