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.