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.

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).

You can install the released version of VIBER from GitHub with:

# install.packages("devtools")
devtools::install_github("caravagnalab/VIBER")

Giulio Caravagna. Cancer Data Science (CDS) Laboratory.