{"Package":"rbiom","Type":"Package","Title":"Integrated Analysis and Visualization of Microbiome Data","Version":"3.1.0","Authors@R":"c(\nperson(\n\"Daniel P.\", \"Smith\",\nemail = \"dansmith01@gmail.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-2479-2044\")),\nperson(\n\"Alkek Center for Metagenomics and Microbiome Research\",\nrole = c(\"cph\", \"fnd\") ))","Description":"A toolkit for working with Biological Observation Matrix ('BIOM') files.\nRead/write all 'BIOM' formats. Compute rarefaction, alpha diversity, and\nbeta diversity (including 'UniFrac'). Summarize counts by taxonomic level.\nSubset based on metadata. Generate visualizations and statistical analyses.","URL":"https://cmmr.github.io/rbiom/, https://github.com/cmmr/rbiom","BugReports":"https://github.com/cmmr/rbiom/issues","License":"MIT + file LICENSE","Encoding":"UTF-8","Depends":"R (>= 4.3.0)","RoxygenNote":"7.3.3","Config/Needs/website":"rmarkdown, phyloseq, npregfast, withr","Config/testthat/edition":"3","Imports":"methods, mgcv, stats, utils, ape, dplyr, ecodive, emmeans,\nfillpattern, ggbeeswarm, ggnewscale, ggplot2, ggrepel, ggtext,\njsonlite, magrittr, patchwork, pillar, plyr, readr, readxl,\nvegan","Suggests":"cli, crayon, ggdensity, glue, h5lite, labeling, lifecycle,\nMatrix, openxlsx, optparse, pkgconfig, prettycode, R6, rlang,\nscales, testthat, tibble, tsne, uwot","NeedsCompilation":"no","Packaged":"2026-05-07 16:43:38 UTC; Daniel","Author":"Daniel P. Smith [aut, cre] (ORCID:\n),\nAlkek Center for Metagenomics and Microbiome Research [cph, fnd]","Maintainer":"Daniel P. Smith ","Repository":"CRAN","Date/Publication":"2026-05-08 08:00:02 UTC","repoType":"cran","tarballUrl":"ftp://cran.r-project.org/pub/R/src/contrib/rbiom_3.1.0.tar.gz","jsonAuthors":[{"name":"Daniel P. Smith","email":"dansmith01@gmail.com","maintainer":true},{"name":"Alkek Center for Metagenomics and Microbiome Research ","email":null,"maintainer":false}],"readme":"\n\n\n# rbiom $\"rbiom$ \n\n\n\n[![cran](https://img.shields.io/cran/v/rbiom?logo=r&label=CRAN)](https://CRAN.R-project.org/package=rbiom)\n[![conda](https://img.shields.io/conda/v/conda-forge/r-rbiom?logo=anaconda&label=conda)](https://anaconda.org/conda-forge/r-rbiom)\n[![downloads](https://cranlogs.r-pkg.org/badges/grand-total/rbiom)](https://cranlogs.r-pkg.org/)\n[![covr](https://img.shields.io/codecov/c/gh/cmmr/rbiom?logo=codecov)](https://app.codecov.io/gh/cmmr/rbiom)\n\n\n`rbiom` is designed for microbiome researchers, providing visualizations\nand statistical analyses from Biological Observation Matrix (BIOM)\nfiles.\n\n## Installation\n\nThe latest stable version can be installed from CRAN.\n\n``` r\ninstall.packages('rbiom')\n```\n\nThe development version is available on GitHub.\n\n``` r\ninstall.packages('pak')\npak::pak('cmmr/rbiom')\n```\n\n## Usage\n\n#### Import and rarefy abundance counts.\n\n``` r\nlibrary(rbiom)\n\ninfile <- system.file(package = 'rbiom', 'extdata', 'hmp50.bz2')\nbiom <- rarefy(infile)\n```\n\n#### Explore associations with metadata.\n\n``` r\nbdiv_ord_plot(biom, stat.by = 'Body Site', facet.by = 'Sex')\n```\n\n![](man/figures/README-bdiv-1.png)\n\n``` r\nadiv_boxplot(biom, x = 'Sex', adiv = c('otu', 'shan'), stat.by = 'Body Site')\n```\n\n![](man/figures/README-bdiv-2.png)\n\n``` r\nsubset(biom, `Body Site` == 'Buccal mucosa') %>% \n taxa_corrplot('Age', taxa = 2, layers = 'ptc', fit = 'lm', test = 'emtrends')\n```\n\n![](man/figures/README-bdiv-3.png)\n\n#### Summarize counts by taxonomic rank.\n\n``` r\ntaxa_heatmap(biom, taxa = 10, tracks = c('body', 'age'))\n```\n\n![](man/figures/README-taxa-1.png)\n\n``` r\ntaxa_stacked(biom, rank = 'Phylum')\n```\n\n![](man/figures/README-taxa-2.png)\n\n``` r\ntaxa_table(biom, 'Phylum')\n#> # A tibble: 294 × 8\n#> .rank .sample .taxa .abundance Age BMI `Body Site` Sex \n#> \n#> 1 Phylum HMP01 Firmicutes 866 22 20 Buccal mucosa Female\n#> 2 Phylum HMP01 Bacteroidetes 202 22 20 Buccal mucosa Female\n#> 3 Phylum HMP01 Actinobacteria 14 22 20 Buccal mucosa Female\n#> 4 Phylum HMP01 Proteobacteria 60 22 20 Buccal mucosa Female\n#> 5 Phylum HMP01 Fusobacteria 33 22 20 Buccal mucosa Female\n#> 6 Phylum HMP01 Tenericutes 0 22 20 Buccal mucosa Female\n#> 7 Phylum HMP02 Firmicutes 814 24 23 Buccal mucosa Male \n#> 8 Phylum HMP02 Bacteroidetes 181 24 23 Buccal mucosa Male \n#> 9 Phylum HMP02 Actinobacteria 49 24 23 Buccal mucosa Male \n#> 10 Phylum HMP02 Proteobacteria 97 24 23 Buccal mucosa Male \n#> # ℹ 284 more rows\n```\n\n## Documentation\n\nThe online manual for `rbiom` is available at\n. It includes a getting started guide,\narticles that explore specific use cases, and reference pages for each\nfunction.\n\n## Community guidelines\n\n### Support\n\nBug reports, feature requests, and general questions can be submitted at\n.\n\n### Contributing\n\nPull requests are welcome. Please ensure contributed code is covered by\ntests and documentation (add additional tests and documentation as\nneeded) and that it passes all automated tests.\n\n## Automated tests\n\nThe following commands will check if `rbiom` passes the bundled testing\nsuite.\n\n``` r\ninstall.packages('testthat')\ntestthat::test_check('rbiom')\n```","jobInfo":{"package":"rbiom","version":"3.1.0","parsingStatus":"success","parserVersion":2,"parsedAt":"2026-05-08T08:30:34+0000"}}

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