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README.Rmd
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---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# VIBER <img src='man/figures/logo.png' align="right" height="139" />
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`VIBER` is a package that implements a variational Bayesian model to fit multi-variate Binomial mixtures. The statistical model is semi-parametric and fit by a variational mean-field approximation to the model posterior. The components are Binomial distributions which can model count data; these can be used to model sequencing counts in the context of cancer, for instance. The package implements methods to fit and visualize clustering results.
#### Citation
[](https://doi.org/10.1038/s41588-020-0675-5)
If you use `VIBER`, please cite:
* G. Caravagna, T. Heide, M.J. Williams, L. Zapata, D. Nichol, K. Chkhaidze, W. Cross, G.D. Cresswell, B. Werner, A. Acar, L. Chesler, C.P. Barnes, G. Sanguinetti, T.A. Graham, A. Sottoriva. Subclonal reconstruction of tumors by using machine learning and population genetics. Nature Genetics 52, 898–907 (2020).
#### Help and support
[](https://caravagnalab.github.io/VIBER)
-----
### Installation
You can install the released version of `VIBER` from
[GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("caravagnalab/VIBER")
```
-----
#### Copyright and contacts
Giulio Caravagna. Cancer Data Science (CDS) Laboratory.
[](mailto:gcaravagn@gmail.com)
[](https://github.com/caravagnalab)
[](https://www.caravagnalab.org/)