{"Package":"rbiom","Type":"Package","Title":"Read/Write, Analyze, and Visualize 'BIOM' Data","Version":"2.2.0","Date":"2025-04-04","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.\nCPU intensive operations are coded in C for speed.","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","LazyData":"true","Depends":"R (>= 4.2.0)","RoxygenNote":"7.3.2","Config/Needs/website":"rmarkdown, phyloseq, npregfast, withr","Config/testthat/edition":"3","Imports":"methods, mgcv, stats, utils, ape, dplyr, emmeans, fillpattern,\nggbeeswarm, ggnewscale, ggplot2, ggrepel, ggtext, jsonlite,\nmagrittr, parallelly, patchwork, pillar, plyr, readr, readxl,\nslam, vegan","Suggests":"cli, crayon, ggdensity, glue, labeling, lifecycle, openxlsx,\noptparse, pkgconfig, prettycode, R6, rlang, scales, testthat,\ntibble, tsne, uwot","NeedsCompilation":"yes","Packaged":"2025-04-04 19:45:52 UTC; Daniel","Author":"Daniel P. Smith [aut, cre] (),\nAlkek Center for Metagenomics and Microbiome Research [cph, fnd]","Maintainer":"Daniel P. Smith ","Repository":"CRAN","Date/Publication":"2025-04-04 20:20:02 UTC","repoType":"cran","tarballUrl":"ftp://cran.r-project.org/pub/R/src/contrib/rbiom_2.2.0.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\n\n\n\n[![cran](https://www.r-pkg.org/badges/version/rbiom)](https://CRAN.R-project.org/package=rbiom)\n[![conda](https://anaconda.org/conda-forge/r-rbiom/badges/version.svg)](https://anaconda.org/conda-forge/r-rbiom)\n[![downloads](https://cranlogs.r-pkg.org/badges/grand-total/rbiom)](https://cranlogs.r-pkg.org/)\n[![dev](https://github.com/cmmr/rbiom/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/cmmr/rbiom/actions/workflows/R-CMD-check.yaml)\n[![covr](https://codecov.io/gh/cmmr/rbiom/graph/badge.svg)](https://app.codecov.io/gh/cmmr/rbiom)\n\n\nThis package is a toolkit for working with Biological Observation Matrix\n(BIOM) files. Features include reading/writing all ‘BIOM’ formats,\nrarefaction, alpha diversity, beta diversity (including ‘UniFrac’),\nsummarizing counts by taxonomic level, subsetting, visualizations, and\nstatistical analysis. All CPU intensive operations are written in C.\n\nReference material is available online at\n\n\nSource code can be found at \n\n## Installation\n\nThe latest stable version can be installed from CRAN.\n\n``` r\ninstall.packages(\"pak\")\npak::pak(\"rbiom\")\n```\n\nThe development version is available on GitHub.\n\n``` r\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\ntaxa_corrplot(biom, x = \"Age\", layers = \"ptc\", taxa = 2, stat.by = \"bod\")\n```\n\n![](man/figures/README-bdiv-3.png)\n\n#### Summarize counts by taxonomic rank.\n\n``` r\ntaxa_heatmap(biom, taxa = 30, 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 856 22 20 Buccal mucosa Female\n#> 2 Phylum HMP01 Bacteroidetes 199 22 20 Buccal mucosa Female\n#> 3 Phylum HMP01 Actinobacteria 16 22 20 Buccal mucosa Female\n#> 4 Phylum HMP01 Proteobacteria 72 22 20 Buccal mucosa Female\n#> 5 Phylum HMP01 Fusobacteria 32 22 20 Buccal mucosa Female\n#> 6 Phylum HMP01 Tenericutes 0 22 20 Buccal mucosa Female\n#> 7 Phylum HMP02 Firmicutes 803 24 23 Buccal mucosa Male \n#> 8 Phylum HMP02 Bacteroidetes 192 24 23 Buccal mucosa Male \n#> 9 Phylum HMP02 Actinobacteria 52 24 23 Buccal mucosa Male \n#> 10 Phylum HMP02 Proteobacteria 96 24 23 Buccal mucosa Male \n#> # ℹ 284 more rows\n```","jobInfo":{"package":"rbiom","version":"2.2.0","parsingStatus":"success","parserVersion":2,"parsedAt":"2025-04-04T22:30:22+0000"}}

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