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 |
| 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:
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