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 human decision with an unsupervised machine learning algorithm (partitioning around medoids, or k-medoids). This algorithm works for any type of microbiome data, provided there is an abundance score for each phylogenetic unit. For validation of this method to several kinds of molecular data and environments, please see Pascoal et al, 2023 (in preparation). Preliminary data suggest this method also works well for non-microbiome data, if there is a species abundance table.
| Version: | 0.1.3 |
| Depends: | R (≥ 2.10) |
| Imports: | cluster, dplyr, ggplot2, purrr, rlang, stats, tidyr, clusterSim, gridExtra |
| Suggests: | knitr, rmarkdown, stringr, testthat (≥ 3.0.0), vegan |
| Published: | 2023-11-17 |
| 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 |
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_0.1.3.tar.gz |
| Windows binaries: | r-devel: ulrb_0.1.3.zip, r-release: ulrb_0.1.3.zip, r-oldrel: ulrb_0.1.3.zip |
| macOS binaries: | r-release (arm64): ulrb_0.1.3.tgz, r-oldrel (arm64): ulrb_0.1.3.tgz, r-release (x86_64): ulrb_0.1.3.tgz, r-oldrel (x86_64): not available |
Linking:
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