Package: rbiom 2.1.2

Daniel P. Smith

rbiom: Read/Write, Analyze, and Visualize 'BIOM' Data

A toolkit for working with Biological Observation Matrix ('BIOM') files. Read/write all 'BIOM' formats. Compute rarefaction, alpha diversity, and beta diversity (including 'UniFrac'). Summarize counts by taxonomic level. Subset based on metadata. Generate visualizations and statistical analyses. CPU intensive operations are coded in C for speed.

Authors:Daniel P. Smith [aut, cre], Alkek Center for Metagenomics and Microbiome Research [cph, fnd]

rbiom_2.1.2.tar.gz
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rbiom_2.1.2.tgz(r-4.4-emscripten)rbiom_2.1.2.tgz(r-4.3-emscripten)
rbiom.pdf |rbiom.html✨
rbiom/json (API)

# Install 'rbiom' in R:
install.packages('rbiom', repos = c('https://cmmr.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cmmr/rbiom/issues

Pkgdown site:https://cmmr.github.io

On CRAN:

Conda:

9.07 score 15 stars 6 packages 117 scripts 25k downloads 2 mentions 134 exports 77 dependencies

Last updated 10 days agofrom:9962903a86. Checks:1 OK, 11 ERROR. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 18 2025
R-4.5-win-x86_64ERRORMar 18 2025
R-4.5-mac-x86_64ERRORMar 18 2025
R-4.5-mac-aarch64ERRORMar 18 2025
R-4.5-linux-x86_64ERRORMar 18 2025
R-4.4-win-x86_64ERRORMar 18 2025
R-4.4-mac-x86_64ERRORMar 18 2025
R-4.4-mac-aarch64ERRORMar 18 2025
R-4.4-linux-x86_64ERRORMar 18 2025
R-4.3-win-x86_64ERRORMar 18 2025
R-4.3-mac-x86_64ERRORMar 18 2025
R-4.3-mac-aarch64ERRORMar 18 2025

Exports:.%<>%%>%adiv_boxplotadiv_corrplotadiv_matrixadiv_statsadiv_tablealpha.divas_rbiomas.percentavailableCoresbdiv_boxplotbdiv_clustersbdiv_corrplotbdiv_distmatbdiv_heatmapbdiv_matrixbdiv_ord_plotbdiv_ord_tablebdiv_statsbdiv_tablebdplybeta.divbiom_mergeblplycommentscomments<-convert_to_phyloseqconvert_to_SEconvert_to_TSEcountscounts<-ddplydepthdepths_barplotdistmat_ord_tabledistmat_statsglimpsehas.phylogenyhas.sequencesidid<-infois.rarefiedldplyleft_joinllplymetadatametadata<-mutatena.omitnsamplesntaxaphylogenyphylogeny<-plot_heatmappullrare_corrplotrare_multiplotrare_stackedrarefyrarefy_colsread_biomread_fastaread_treeread.biomread.fastaread.treerelocaterenamerepairrescale_colsrescale_rowssample_applysample_subsetsample_sumssample.namessample.names<-sample.sumsselectsequencessequences<-sliceslice_headslice_maxslice_minslice_sampleslice_tailstats_boxplotstats_corrplotstats_tablesubset_taxasubtreetaxa_applytaxa_boxplottaxa_clusterstaxa_corrplottaxa_heatmaptaxa_maptaxa_matrixtaxa_maxtaxa_meanstaxa_stackedtaxa_statstaxa_sumstaxa_tabletaxa.meanstaxa.namestaxa.names<-taxa.rankstaxa.ranks<-taxa.rolluptaxa.sumstaxonomytaxonomy<-tipstop_taxatop.taxatree_subsetunifracwrite_biomwrite_countswrite_fastawrite_metadatawrite_mothurwrite_qiime2write_taxonomywrite_treewrite_xlsxwrite.biomwrite.fastawrite.treewrite.xlsx

Dependencies:apebeeswarmbitbit64cellrangerclicliprclustercolorspacecommonmarkcpp11crayoncurldigestdplyremmeansestimabilityfansifarverfillpatterngenericsggbeeswarmggnewscaleggplot2ggrepelggtextgluegridtextgtablehmsisobandjpegjsonlitelabelinglatticelifecyclemagrittrmarkdownMASSMatrixmgcvmunsellmvtnormnlmenumDerivparallellypatchworkpermutepillarpkgconfigplyrpngprettyunitsprogressR6RColorBrewerRcppreadrreadxlrematchrlangscalesslamstringistringrtibbletidyselecttzdbutf8vctrsveganviporviridisLitevroomwithrxfunxml2

Readme and manuals

Help Manual

Help pageTopics
Visualize alpha diversity with boxplots.adiv_boxplot
Visualize alpha diversity with scatterplots and trendlines.adiv_corrplot
Create a matrix of samples x alpha diversity metrics.adiv_matrix
Test alpha diversity for associations with metadata.adiv_stats
Calculate the alpha diversity of each sample.adiv_table
Convert a variety of data types to an rbiom object.as_rbiom
Convert an rbiom object to a base R list.as.list.rbiom
Convert an rbiom object to a simple count matrix.as.matrix.rbiom
Longitudinal Stool Samples from Infants (n = 2,684)babies
Visualize BIOM data with boxplots.bdiv_boxplot
Cluster samples by beta diversity k-means.bdiv_clusters
Visualize beta diversity with scatterplots and trendlines.bdiv_corrplot
Display beta diversities in an all vs all grid.bdiv_heatmap
Ordinate samples and taxa on a 2D plane based on beta diversity distances.bdiv_ord_plot
Calculate PCoA and other ordinations, including taxa biplots and statistics.bdiv_ord_table
Test beta diversity for associations with metadata.bdiv_stats
Distance / dissimilarity between samples.bdiv_distmat bdiv_matrix bdiv_table
Apply a function to each subset of an rbiom object.bdply blply
Combine several rbiom objects into one.biom_merge
Convert biom data to an external package class.convert_to convert_to_phyloseq convert_to_SE convert_to_TSE
Run ordinations on a distance matrix.distmat_ord_table
Run statistics on a distance matrix vs a categorical or numeric variable.distmat_stats
Export data to QIIME 2 or mothur.export write_mothur write_qiime2
Global Enteric Multicenter Study (n = 1,006)gems
Get a glimpse of your metadata.glimpse.rbiom
Human Microbiome Project - demo dataset (n = 50)hmp50
Create, modify, and delete metadata fields.modify_metadata mutate.rbiom rename.rbiom
Create a heatmap with tracks and dendrograms from any matrix.plot_heatmap
Map sample names to metadata field values.pull.rbiom
Visualize rarefaction curves with scatterplots and trendlines.rare_corrplot
Combines rare_corrplot and rare_stacked into a single figure.rare_multiplot
Visualize the number of observations per sample.rare_stacked
Rarefy OTU counts.rarefy
Transform a counts matrix.rarefy_cols rescale_cols rescale_rows
Parse counts, metadata, taxonomy, and phylogeny from a BIOM file.read_biom
Parse a fasta file into a named character vector.read_fasta
Read a newick formatted phylogenetic tree.read_tree
Summarize the taxa observations in each sample.sample_apply sample_sums
Subset to a specific number of samples.slice.rbiom slice_head.rbiom slice_max.rbiom slice_metadata slice_min.rbiom slice_sample.rbiom slice_tail.rbiom
Visualize categorical metadata effects on numeric values.stats_boxplot
Visualize regression with scatterplots and trendlines.stats_corrplot
Run non-parametric statistics on a data.frame.stats_table
Subset an rbiom object by sample names, OTU names, metadata, or taxonomy.na.omit.rbiom subset subset.rbiom subset_taxa [.rbiom
Visualize BIOM data with boxplots.taxa_boxplot
Cluster samples by taxa abundances k-means.taxa_clusters
Visualize taxa abundance with scatterplots and trendlines.taxa_corrplot
Display taxa abundances as a heatmap.taxa_heatmap
Map OTUs names to taxa names at a given rank.taxa_map
Display taxa abundances as a stacked bar graph.taxa_stacked
Test taxa abundances for associations with metadata.taxa_stats
Get summary taxa abundances.taxa_apply taxa_means taxa_sums
Taxa abundances per sample.taxa_matrix taxa_table
Create a subtree by specifying tips to keep.tree_subset
Evaluate expressions on metadata.with with.rbiom within.rbiom
Save an rbiom object to a file.write_biom write_counts write_fasta write_metadata write_taxonomy write_tree write_xlsx