Package: ulrb 0.1.8

ulrb: Unsupervised Learning Based Definition of Microbial Rare Biosphere

A tool to define the 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 an abundance table. This method also works for non-microbiome data.

Authors:Francisco Pascoal [aut, cre], Paula Branco [aut], Luís Torgo [aut], Rodrigo Costa [aut], Catarina Magalhães [aut]

ulrb_0.1.8.tar.gz
ulrb_0.1.8.zip(r-4.7)ulrb_0.1.8.zip(r-4.6)ulrb_0.1.8.zip(r-4.5)
ulrb_0.1.8.tgz(r-4.6-any)ulrb_0.1.8.tgz(r-4.5-any)
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ulrb_0.1.8.tgz(r-4.5-emscripten)
ulrb.pdf |ulrb.html✨
ulrb/json (API)

# Install 'ulrb' in R:

install.packages('ulrb', repos = c('https://pascoalf.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/pascoalf/ulrb/issues

Pkgdown/docs site:https://pascoalf.github.io

Datasets:

nice - V4-V5 16S rRNA gene amplicons, clean OTU table
nice_env - Metadata of samples from OTU tables
nice_raw - V4-V5 16S rRNA gene amplicons, raw OTU table
nice_tidy - V4-V5 16S rRNA gene amplicons, clean OTU table in tidy/long format

On CRAN:

6.00 score 6 stars 14 scripts 351 downloads 11 exports 42 dependencies

Last updated from:e8271ff0b9. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	201
source / vignettes	OK	289
linux-release-x86_64	OK	201
macos-release-arm64	OK	165
macos-oldrel-arm64	OK	190
windows-devel	OK	164
windows-release	OK	141
windows-oldrel	OK	149
wasm-release	OK	132

Exports:check_avgSil check_CH check_DB define_rb evaluate_k evaluate_sample_k plot_ulrb plot_ulrb_clustering plot_ulrb_silhouette prepare_tidy_data suggest_k

Dependencies:ade4 class cli cluster clusterSim cpp11 dplyr e1071 farver generics ggplot2 glue gridExtra gtable isoband labeling lattice lifecycle magrittr MASS pillar pixmap pkgconfig proxy purrr R6 RColorBrewer Rcpp RcppArmadillo rlang S7 scales sp stringi stringr tibble tidyr tidyselect utf8 vctrs viridisLite withr

Alternative classifications with ulrb

Rendered fromexplore-classifications.Rmdusingknitr::rmarkdownon Apr 03 2026.

Last update: 2025-05-14
Started: 2023-06-06

Glossary

Rendered fromGlossary.Rmdusingknitr::rmarkdownon Apr 03 2026.

Last update: 2023-11-01
Started: 2023-09-15

Integration of ulrb in a simple microbial ecology workflow

Rendered fromeco-analysis.Rmdusingknitr::rmarkdownon Apr 03 2026.

Last update: 2025-07-07
Started: 2023-04-12

Tutorial to define rare biosphere with ulrb

Rendered fromulrb-vignet.Rmdusingknitr::rmarkdownon Apr 03 2026.

Last update: 2025-05-14
Started: 2023-01-10

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
ulrb: Unsupervised Learning Based Definition of Microbial Rare Biosphere	ulrb-package
Check average Silhouette score index	check_avgSil
Check Calinski-Harabasz index	check_CH
Check Davies-Bouldin Index	check_DB
Define Rare Biosphere	define_rb
Evaluate k from all samples in a dataset	evaluate_k
Evaluate sample k	evaluate_sample_k
V4-V5 16S rRNA gene amplicons, clean OTU table (N-ICE, 2015)	nice
Metadata of samples from OTU tables (N-ICE, 2015)	nice_env
V4-V5 16S rRNA gene amplicons, raw OTU table (N-ICE, 2015)	nice_raw
V4-V5 16S rRNA gene amplicons, clean OTU table in tidy/long format (N-ICE, 2015)	nice_tidy
Plot ulrb clustering results and silhouette scores	plot_ulrb
Plot Rank Abundance Curve of classification results	plot_ulrb_clustering
Plot silhouette scores from clustering results	plot_ulrb_silhouette
Prepare data in tidy format	prepare_tidy_data
Suggest k	suggest_k