Package: ulrb 0.1.6
Francisco Pascoal
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.
Authors:
ulrb_0.1.6.tar.gz
ulrb_0.1.6.zip(r-4.5)ulrb_0.1.6.zip(r-4.4)ulrb_0.1.6.zip(r-4.3)
ulrb_0.1.6.tgz(r-4.4-any)ulrb_0.1.6.tgz(r-4.3-any)
ulrb_0.1.6.tar.gz(r-4.5-noble)ulrb_0.1.6.tar.gz(r-4.4-noble)
ulrb_0.1.6.tgz(r-4.4-emscripten)ulrb_0.1.6.tgz(r-4.3-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
Last updated 19 hours agofrom:ed4b506121. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 17 2024 |
| R-4.5-win | OK | Sep 17 2024 |
| R-4.5-linux | OK | Sep 17 2024 |
| R-4.4-win | OK | Sep 17 2024 |
| R-4.4-mac | OK | Sep 17 2024 |
| R-4.3-win | OK | Sep 17 2024 |
| R-4.3-mac | OK | Sep 17 2024 |
Exports:check_avgSilcheck_CHcheck_DBdefine_rbevaluate_kevaluate_sample_kplot_ulrbplot_ulrb_clusteringplot_ulrb_silhouetteprepare_tidy_datasuggest_k
Dependencies:ade4classcliclusterclusterSimcolorspacecpp11dplyre1071fansifarvergenericsggplot2gluegridExtragtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpixmappkgconfigproxypurrrR6RColorBrewerRcppRcppArmadillorlangscalesspstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr
Alternative classifications with ulrb
Rendered fromexplore-classifications.Rmdusingknitr::rmarkdownon Sep 17 2024.Last update: 2024-06-24
Started: 2023-06-06
Glossary
Rendered fromGlossary.Rmdusingknitr::rmarkdownon Sep 17 2024.Last update: 2023-11-01
Started: 2023-09-15
Integration of ulrb in a simple microbial ecology workflow
Rendered fromeco-analysis.Rmdusingknitr::rmarkdownon Sep 17 2024.Last update: 2024-06-24
Started: 2023-04-12
Tutorial to define rare biosphere with ulrb
Rendered fromulrb-vignet.Rmdusingknitr::rmarkdownon Sep 17 2024.Last update: 2024-09-13
Started: 2023-01-10
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 |
