Package: breakaway 4.8.4

breakaway: Species Richness Estimation and Modeling

Understanding the drivers of microbial diversity is an important frontier of microbial ecology, and investigating the diversity of samples from microbial ecosystems is a common step in any microbiome analysis. 'breakaway' is the premier package for statistical analysis of microbial diversity. 'breakaway' implements the latest and greatest estimates of species richness, described in Willis and Bunge (2015) <doi:10.1111/biom.12332>, Willis et al. (2017) <doi:10.1111/rssc.12206>, and Willis (2016) <arxiv:1604.02598>, as well as the most commonly used estimates, including the objective Bayes approach described in Barger and Bunge (2010) <doi:10.1214/10-BA527>.

Authors:Amy D Willis [aut, cre], Bryan D Martin [aut], Pauline Trinh [aut], Sarah Teichman [aut], David Clausen [aut], Kathryn Barger [aut], John Bunge [aut]

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breakaway.pdf |breakaway.html✨
breakaway/json (API)

# Install 'breakaway' in R:
install.packages('breakaway', repos = c('https://adw96.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/adw96/breakaway/issues

Datasets:
  • apples - (Data) Frequency count table of soil microbes in an apples orchard.
  • hawaii - (Data) Frequency count table of soil microbes in Hawaii.
  • pasolli_et_al - (Data) Data frame of covariate information about pasolli_et_al.
  • soil_phylo - (Data) Data frame of soil data from whitman_et_al.
  • toy_metadata - (Data) Data frame of covariate information about toy_otu_table.
  • toy_otu_table - (Data) A toy OTU table.
  • toy_taxonomy - (Data) The taxonomy of the OTUs in 'toy_otu_table'.

On CRAN:

8.16 score 68 stars 204 scripts 457 downloads 45 exports 78 dependencies

Last updated 12 months agofrom:6d3c912963. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 26 2024
R-4.5-winOKOct 26 2024
R-4.5-linuxOKOct 26 2024
R-4.4-winOKOct 26 2024
R-4.4-macOKOct 26 2024
R-4.3-winOKOct 26 2024
R-4.3-macOKOct 26 2024

Exports:%>%alpha_estimatealpha_estimatesbettabetta_lincombetta_picbetta_randombreakawaybreakaway_nof1build_frequency_count_tableschao_bungechao_shenchao1chao1_bcconvertF_testgood_turingkempmake_design_matrixmake_frequency_count_tableobjective_bayes_geometricobjective_bayes_mixedgeoobjective_bayes_negbinobjective_bayes_poissonpoisson_modelpoisson_model_nof1proportions_insteadrnbinomtablerztnbinomtablesample_inverse_simpsonsample_richnesssample_shannonsample_shannon_esample_simpsonsample_size_estimatesample_size_figuretest_submodeltrue_ginitrue_hilltrue_inverse_simpsontrue_shannontrue_shannon_etrue_simpsonwlrm_transformedwlrm_untransformed

Dependencies:ade4apeaskpassBiobaseBiocGenericsbiomformatBiostringsbootcliclustercodetoolscolorspacecpp11crayoncurldata.tabledigestfansifarverforeachGenomeInfoDbGenomeInfoDbDataggplot2gluegtablehttrigraphIRangesisobanditeratorsjsonlitelabelinglatticelifecyclelme4magrittrMASSMatrixmgcvmimeminqamulttestmunsellnlmenloptropensslpermutephyloseqpillarpixmappkgconfigplyrR6RColorBrewerRcppRcppArmadilloRcppEigenreshape2rhdf5rhdf5filtersRhdf5librlangS4VectorsscalesspstringistringrsurvivalsystibbleUCSC.utilsutf8vctrsveganviridisLitewithrXVectorzlibbioc

Getting started with breakaway

Amy Willis

Rendered frombreakaway.Rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2022-10-04
Started: 2017-09-21

Introduction to diversity estimation

Amy Willis

Rendered fromintro-diversity-estimation.Rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2022-11-22
Started: 2019-07-31

Introduction to hypothesis testing for diversity

Amy Willis

Rendered fromdiversity-hypothesis-testing.Rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2022-11-22
Started: 2019-08-15

Readme and manuals

Help Manual

Help pageTopics
alpha_estimatealpha_estimate
alpha_estimatesalpha_estimates
(Data) Frequency count table of soil microbes in an apples orchard.apples
Modelling total diversity with bettabetta
Confidence intervals and testing for linear combinations of fixed effects estimated via betta() or betta_random()betta_lincom
function for plotting total diversitybetta_pic
modelling total diversity with random effectsbetta_random
Species richness estimation with breakawaybreakaway
species richness estimation without singletonsbreakaway_nof1
Build frequency count tables from an OTU tablebuild_frequency_count_tables
Chao-Bunge species richness estimatorchao_bunge
The Chao-Shen estimate of Shannon diversitychao_shen
Chao1 species richness estimatorchao1
Bias-corrected Chao1 species richness estimatorchao1_bc
Run some basic checks on a possible frequency count tablecheck_format
convert between different inputs for alpha-diversity estimatesconvert
Find a cut-off for estimates relying on contiguous countscutoff_wrap
Conduct F test of null hypothesis LB = 0 using output from betta() or betta_random()F_test
Calculate F statistic under null hypothesis LB = 0 using output from betta() or betta_random()get_F_stat
The Good-Turing estimate of species richnessgood_turing
(Data) Frequency count table of soil microbes in Hawaii.hawaii
Species richness estimation with Kemp-type modelskemp
Make design matrixmake_design_matrix
Draw frequency count subtables from an OTU tablemake_frequency_count_table
Estimate species richness with an objective Bayes method using a geometric modelobjective_bayes_geometric
Objective Bayes species richness estimate with the mixed-geometric modelobjective_bayes_mixedgeo
Objective Bayes species richness estimate with the Negative Binomial modelobjective_bayes_negbin
Objective Bayes species richness estimate with the Poisson modelobjective_bayes_poisson
(Data) Data frame of covariate information about pasolli_et_al.pasolli_et_al
Wrapper for phyloseq objectsphyseq_wrap
Plot function for alpha_estimates classplot.alpha_estimates
PoissonModelpoisson_model
PoissonModelNof1poisson_model_nof1
OTU table to relative abundancesproportions_instead
Negative binomially distributed frequency count tables.rnbinomtable
beta version: Zero-truncated negative binomially distributed frequency count tables.rztnbinomtable
Plug-in Inverse Simpson diversitysample_inverse_simpson
Sample richness estimatorsample_richness
Plug-in Shannon diversitysample_shannon
Plug-in Shannon's E ("Equitability")sample_shannon_e
Plug-in Simpson diversitysample_simpson
Estimate the sample size needed to do an unpaired one-way test using bettasample_size_estimate
Plot the power obtained with sample sizesample_size_figure
Simulate from a fitted betta modelsimulate_betta
Simulate from a fitted betta_random modelsimulate_betta_random
(Data) Data frame of soil data from whitman_et_al.soil_phylo
Conduct F test of null hypothesis LB = 0 using output from betta() or betta_random()test_submodel
(Data) Data frame of covariate information about toy_otu_table.toy_metadata
(Data) A toy OTU table.toy_otu_table
(Data) The taxonomy of the OTUs in `toy_otu_table`.toy_taxonomy
Calculate the true Gini-Simpson indextrue_gini
Calculate the true Hill numberstrue_hill
Calculate the true Inverse Simpson indextrue_inverse_simpson
Calculate the true Shannon index based on proportionstrue_shannon
Calculate the true Shannon's equitability indextrue_shannon_e
Calculate the true Simpson indextrue_simpson
The transformed weighted linear regression estimator for species richness estimationwlrm_transformed
The untransformed weighted linear regression estimator for species richness estimationwlrm_untransformed