Package: BRACoD.R 0.0.2.0
Adrian Verster
BRACoD.R: BRACoD: Bayesian Regression Analysis of Compositional Data
The goal of this method is to identify associations between bacteria and an environmental variable in 16S or other compositional data. The environmental variable is any variable which is measure for each microbiome sample, for example, a butyrate measurement paired with every sample in the data. Microbiome data is compositional, meaning that the total abundance of each sample sums to 1, and this introduces severe statistical distortions. This method takes a Bayesian approach to correcting for these statistical distortions, in which the total abundance is treated as an unknown variable. This package runs the python implementation using reticulate.
Authors:
BRACoD.R_0.0.2.0.tar.gz
BRACoD.R_0.0.2.0.tar.gz(r-4.5-noble)BRACoD.R_0.0.2.0.tar.gz(r-4.4-noble)
BRACoD.R_0.0.2.0.tgz(r-4.4-emscripten)BRACoD.R_0.0.2.0.tgz(r-4.3-emscripten)
BRACoD.R.pdf |BRACoD.R.html✨
BRACoD.R/json (API)
| # Install 'BRACoD.R' in R: |
| install.packages('BRACoD.R', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- df_counts_obesity - Example microbiome data
- df_scfa - Example microbiome data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:b0ad5b5a45. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 01 2024 |
| R-4.5-linux | OK | Sep 01 2024 |
Exports:convergence_testsinstall_bracodremove_nullrun_bracodscale_countsscoresimulate_microbiome_countssummarize_tracethreshold_count_data
Dependencies:herejsonlitelatticeMatrixpngrappdirsRcppRcppTOMLreticulaterlangrprojrootwithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Perform convergence tests on the p and beta variables | convergence_tests |
| Install BRACoD in python | install_bracod |
| Example microbiome data | df_counts_obesity df_counts_obesity,df_scfa df_scfa obesity |
| Remove NULL values in your OTU and environmental variable | remove_null |
| Run the main BRACoD algorithm | run_bracod |
| Normalize OTU counts and add a pseudo count | scale_counts |
| Score the results of BRACoD | score |
| Simulate microbiome counts | simulate_microbiome_counts |
| Summarize the results of BRACoD | summarize_trace |
| Threshold your microbiome counts data | threshold_count_data |