BASCULE is a Bayesian model to fit multiple signature types from multiple patients, leveraging a pre-existing catalogue of known signatures such as COSMIC. BASCULE searches for known signatures from the input catalogue as well as for new signatures that outside the catalogue, accounting for hidden structure in the input data (e.g., distinct tumour types). Moreover, bascule performs tensor clustering to retrieve latent groups in the input cohort from the exposures of multiple signature types jointly. The model uses non-negative matrix factorisation and variational inference implemented in the pybascule Python package.
If you use bascule, please cite:
- Buscaroli, E., Sadr, A., Bergamin, R. et al. BASCULE: bayesian inference and clustering of mutational signatures leveraging biological priors. Genome Biol (2025).
You can install the released version of bascule from
GitHub with:
# install.packages("devtools")
devtools::install_github("caravagnalab/bascule")If you want to fit your data with bascule, you also need to install the required Python dependencies. Please follow the instructions in the Get Started article.
Elena Buscaroli, Azad Sadr, Giulio Caravagna. Cancer Data Science (CDS) Laboratory, University of Trieste, Italy.
