https://github.com/drisso/learn2count
Structure learning based for zero-inflated negative binomial data
https://github.com/drisso/learn2count
Last synced: 9 months ago
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Structure learning based for zero-inflated negative binomial data
- Host: GitHub
- URL: https://github.com/drisso/learn2count
- Owner: drisso
- Created: 2018-12-07T09:20:24.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2024-07-11T13:11:24.000Z (almost 2 years ago)
- Last Synced: 2024-12-17T13:51:37.337Z (over 1 year ago)
- Language: R
- Size: 120 KB
- Stars: 12
- Watchers: 3
- Forks: 4
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- Changelog: NEWS.md
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README
# The `learn2count` package
This package implements algorithms for structure learning of graphical models for count data.
The function `PCzinb` implements three algorithms to estimate the structure of a graph from the input data.
The function `simdata` can be used to simulate data.
## Installation
The preferred way to install the package is
```{r}
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("drisso/learn2count")
```
## Usage
Please, see the [vignette](vignettes/intro.Rmd) for detailed examples of the package usage.
## Versions of this package
The analyses and figures of the Nguyen et al. (2023) paper were done with package version `0.1.3`, which can be found [here](https://github.com/drisso/learn2count/releases/tag/v0.1.3). Please use this version to reproduce the results of the paper.
The analyses and figures of the Nguyen et al. (2022) paper were done with package version `0.3.0`, which can be found [here](https://github.com/drisso/learn2count/releases/tag/v0.3.0). Please use this version to reproduce the results of the paper.
For virtually all other uses, we recommend using the latest stable version of the package (corresponding to the `master` branch).
## References
Nguyen, Van den Berge, Chiogna, Risso (2023). [Structure learning for zero- inflated counts, with an application to single-cell RNA sequencing data](https://projecteuclid.org/journals/annals-of-applied-statistics/volume-17/issue-3/Structure-learning-for-zero-inflated-counts-with-an-application-to/10.1214/23-AOAS1732.full). _Annals of Applied Statistics_.
Nguyen, Chiogna, Risso, Banzato (2024). Guided structure learning of DAGs for count data. _Statistical Modelling. In print_. [Preprint](https://doi.org/10.48550/arXiv.2206.09754).