Package: rbiom 2.0.0.9137

Daniel P. Smith

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

A toolkit for working with Biological Observation Matrix ('BIOM') files. Features include reading/writing all 'BIOM' formats, rarefaction, alpha diversity, beta diversity (including 'UniFrac'), summarizing counts by taxonomic level, subsetting, visualizations, and statistical analysis. All CPU intensive operations are written in C.

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

rbiom_2.0.0.9137.tar.gz
rbiom_2.0.0.9137.zip(r-4.5)rbiom_2.0.0.9137.zip(r-4.4)rbiom_2.0.0.9137.zip(r-4.3)
rbiom_2.0.0.9137.tgz(r-4.4-x86_64)rbiom_2.0.0.9137.tgz(r-4.4-arm64)rbiom_2.0.0.9137.tgz(r-4.3-x86_64)rbiom_2.0.0.9137.tgz(r-4.3-arm64)
rbiom_2.0.0.9137.tar.gz(r-4.5-noble)rbiom_2.0.0.9137.tar.gz(r-4.4-noble)
rbiom_2.0.0.9137.tgz(r-4.4-emscripten)rbiom_2.0.0.9137.tgz(r-4.3-emscripten)
 |rbiom.html✨
rbiom/json (API)

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

Peer review:

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

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • babies - Longitudinal Stool Samples from Infants
  • gems - Global Enteric Multicenter Study
  • hmp50 - Human Microbiome Project - demo dataset

On CRAN:

130 exports 11 stars 3.27 score 70 dependencies 8 dependents 2 mentions 155 scripts 484 downloads

Last updated 1 months agofrom:24516c5b69. Checks:ERROR: 9. Indexed: yes.

TargetResultDate
Doc / VignettesFAILSep 12 2024
R-4.5-win-x86_64ERRORSep 12 2024
R-4.5-linux-x86_64ERRORSep 12 2024
R-4.4-win-x86_64ERRORSep 12 2024
R-4.4-mac-x86_64ERRORSep 12 2024
R-4.4-mac-aarch64ERRORSep 12 2024
R-4.3-win-x86_64ERRORSep 12 2024
R-4.3-mac-x86_64ERRORSep 12 2024
R-4.3-mac-aarch64ERRORSep 12 2024

Exports:.%<>%%>%adiv_boxplotadiv_corrplotadiv_matrixadiv_statsadiv_tablealpha.divas_rbiomas.percentbdiv_boxplotbdiv_clustersbdiv_corrplotbdiv_distmatbdiv_heatmapbdiv_matrixbdiv_ord_plotbdiv_ord_tablebdiv_statsbdiv_tablebdplybeta.divbiom_file_formatbiom_mergeblplycommentscomments<-convert_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_tablesubtreetaxa_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_taxonomywrite_treewrite_xlsxwrite.biomwrite.fastawrite.treewrite.xlsx

Dependencies:apebackportsbeeswarmbroomcliclustercolorspacecommonmarkcpp11curldigestdplyremmeansestimabilityfansifarvergenericsggbeeswarmggnewscaleggplot2ggrepelggtextgluegridtextgtableisobandjpegjsonlitelabelinglatticelifecyclemagrittrmarkdownMASSMatrixmgcvmunsellmvtnormnlmenumDerivpatchworkpermutepillarpkgconfigplyrpngpurrrR.methodsS3R.ooR.utilsR6RColorBrewerRcppRcppParallelrlangscalesslamstringistringrtibbletidyrtidyselectutf8vctrsveganviporviridisLitewithrxfunxml2

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
Longitudinal Stool Samples from Infants (n = 2,684)babies
Visualize BIOM data with boxplots.bdiv_boxplot
Define sample PAM clusters from beta diversity.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 an rbiom object to a SummarizedExperiment object.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
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 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 or metadata.na.omit.rbiom subset subset.rbiom [.rbiom
Visualize BIOM data with boxplots.taxa_boxplot
Define sample kmeans clusters from taxa abundances.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