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nbfar: Negative Binomial Factor Regression Models ('nbfar')

We developed a negative binomial factor regression model to estimate structured (sparse) associations between a feature matrix X and overdispersed count data Y. With 'nbfar', microbiome count data Y can be used, for example, to associate host or environmental covariates with microbial abundances. Currently, two models are available: a) Negative Binomial reduced rank regression (NB-RRR), b) Negative Binomial co-sparse factor regression (NB-FAR). Please refer the manuscript 'Mishra, A. K., & Müller, C. L. (2021). Negative Binomial factor regression with application to microbiome data analysis. bioRxiv.' for more details.

Version: 0.1
Depends: R (≥ 3.5.0), stats, utils
Imports: Rcpp (≥ 0.12.9), MASS, magrittr, rrpack, glmnet, RcppParallel, mpath
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Suggests: rmarkdown, knitr, spelling
Published: 2022-02-22
DOI: 10.32614/CRAN.package.nbfar
Author: Aditya Mishra [aut, cre], Christian Mueller [aut]
Maintainer: Aditya Mishra <amishra at flatironinstitute.org>
License: GPL (≥ 3.0)
URL: https://github.com/amishra-stats/nbfar, https://www.biorxiv.org/content/10.1101/2021.11.29.470304v1
NeedsCompilation: yes
Language: en-US
CRAN checks: nbfar results

Documentation:

Reference manual: nbfar.pdf
Vignettes: Negative Binomial factor regression with application to microbiome data analysis

Downloads:

Package source: nbfar_0.1.tar.gz
Windows binaries: r-devel: nbfar_0.1.zip, r-release: nbfar_0.1.zip, r-oldrel: nbfar_0.1.zip
macOS binaries: r-release (arm64): nbfar_0.1.tgz, r-oldrel (arm64): nbfar_0.1.tgz, r-release (x86_64): nbfar_0.1.tgz, r-oldrel (x86_64): nbfar_0.1.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=nbfar to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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