Package: banocc 1.37.0

George Weingart

banocc: Bayesian ANalysis Of Compositional Covariance

BAnOCC is a package designed for compositional data, where each sample sums to one. It infers the approximate covariance of the unconstrained data using a Bayesian model coded with `rstan`. It provides as output the `stanfit` object as well as posterior median and credible interval estimates for each correlation element.

Authors:Emma Schwager [aut, cre], Curtis Huttenhower [aut]

banocc_1.37.0.tar.gz
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banocc_1.37.0.tgz(r-4.6-any)banocc_1.37.0.tgz(r-4.5-any)
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manual.pdf |manual.html✨
card.svg |card.png
banocc/json (API)

# Install 'banocc' in R:

install.packages('banocc', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

compositions_hard_null - Simulated compositional data with no feature correlations
compositions_neg_spike - Simulated compositional data with a negative count correlation
compositions_null - Simulated compositional data with no feature correlations
compositions_pos_spike - Simulated compositional data with a positive count correlation
counts_hard_null - Simulated count data with no feature correlations
counts_neg_spike - Simulated count data with one negative feature correlation
counts_null - Simulated count data with no feature correlations
counts_pos_spike - Simulated count data with one positive feature correlation

On BioConductor:banocc-1.37.0(bioc 3.24)banocc-1.36.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

immunooncology metagenomics software bayesian

4.15 score 14 scripts 452 downloads 3 exports 51 dependencies

Last updated from:1f631fc2dc. Checks:1 WARNING, 4 NOTE, 2 OK, 3 ERROR. Indexed: yes.

Target	Result	Time
bioc-checks	WARNING	177
linux-devel-x86_64	NOTE	406
source / vignettes	OK	292
linux-release-x86_64	NOTE	268
macos-release-arm64	NOTE	181
macos-oldrel-arm64	NOTE	123
windows-devel	ERROR	227
windows-release	ERROR	228
windows-oldrel	ERROR	239
wasm-release	OK	160

Exports:banocc_model get_banocc_output run_banocc

Dependencies:abind backports BH callr checkmate cli coda cpp11 desc distributional farver generics ggplot2 glue gridExtra gtable inline isoband labeling lattice lifecycle loo magrittr matrixStats mvtnorm numDeriv pillar pkgbuild pkgconfig posterior processx ps QuickJSR R6 RColorBrewer Rcpp RcppEigen RcppParallel rlang rstan S7 scales StanHeaders stringi stringr tensorA tibble utf8 vctrs viridisLite withr

Introduction to BAnOCC (Bayesian Analaysis Of Compositional Covariance)

Emma Schwager

Rendered frombanocc-vignette.Rmdusingknitr::rmarkdownon May 29 2026.

Last update: 2022-04-20
Started: 2017-03-31

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
banocc: A package for Bayesian ANalysis of Compositional Correlation	banocc-package banocc
The stan model used in the Bayesian fit	banocc_model
Simulated compositional data with no feature correlations	compositions_hard_null
Simulated compositional data with a negative count correlation	compositions_neg_spike
Simulated compositional data with no feature correlations	compositions_null
Simulated compositional data with a positive count correlation	compositions_pos_spike
Simulated count data with no feature correlations	counts_hard_null
Simulated count data with one negative feature correlation	counts_neg_spike
Simulated count data with no feature correlations	counts_null
Simulated count data with one positive feature correlation	counts_pos_spike
Takes a model fit from BAnOCC, evaluates convergence and generates appropriate convergence metrics and inference	get_banocc_output
Runs BAnOCC to fit the model and generate appropriate convergence metrics and inference.	run_banocc