Embedded Files
Our tools are hosted at the laboratory GitHub webpage. We use the issues tracking system to provide support to users that experience challenges in using our tools.
In preparation
In preparation
evoverse.datasets - Data package
Input datasets and computation results from a number of packages that we have developed.
lineaGT/pylineagt - Bayesian multi-lineage inference from gene therapy assays
Multi-lineage inference from Gene Therapy assays that use insertional mutagenesis and somatic mutations to track clonal expansions in the hematopoietic compartment. Leveraging Bayesian models,Pyro implementation and stochastic variational inference (double package)
tapacloth - Classification of cancer mutation clonality and zygosity from target sequencing
A model that uses panel read counts data to determine the clonality status of tumour mutations while estimating their zygosity, fundamental to understand the complex interplay between somatic mutations and aneuploidy from panel data.
basilica/pybasilica - Bayesian somatic signature learning with a catalogue
A semi-supervised Bayesian hierarchical model to detect somatic signatures using a catalogue, with a Pyro implementation and stochastic variational inference (double package).
Stable releases
Stable releases
A Copy Number Alterations quality check package to assess the concordance between clonal and subclonal copy number segments and somatic mutations called from bulk sequencing.
- Alice Antonello, Riccardo Bergamin, Nicola Calonaci, Jacob Househam, Salvatore Milite, Marc J Williams, Fabio Anselmi, Alberto d’Onofrio, Vasavi Sundaram, Alona Sosinsky, William CH Cross, Giulio Caravagna. Computational validation of clonal and subclonal copy number alterations from bulk tumor sequencing using CNAqc. Genome Biology 25 (38), 1(2024)
A method to determine the contamination of a tumour sample by normal cells, which can be used to quality control tumour-normal designs and confirm that normal samples are not contaminated by tumour variants.
- Jonathan Mitchell, Salvatore Milite, Jack Bartram, Susan Walker, Nadezda Volkova, Olena Yavorska, Magdalena Zarowiecki, Jane Chalker, Rebecca Thomas, Luca Vago, Alona Sosinsky, Giulio Caravagna. Clinical application of tumour-in-normal contamination assessment from whole genome sequencing. Nature Communications 15, 323 (2024).
A Bayesian method to call Copy Number Alterations from single-cell RNA and ATAC sequencing data, supporting multi-omics assays and cell clustering.
- Salvatore Milite, Riccardo Bergamin, Lucrezia Patruno, Nicola Calonaci, Giulio Caravagna. A Bayesian method to cluster single-cell RNA sequencing data using Copy Number Alterations. Bioinformatics Volume 38, Issue 9, 1 May 2022, Pages 2512–2518
- Lucrezia Patruno, Salvatore Milite, Riccardo Bergamin Nicola Calonaci, Alberto D’Onofrio, Fabio Anselmi, Marco Antoniotti, Alex Graudenzi, Giulio Caravagna. A Bayesian method to infer copy number clones from single-cell RNA and ATAC sequencing.. PLoS Computational Biology 19(11): e1011557, 2023.
Tumour subclonal deconvolution from whole-genome DNA sequencing, exploiting joint Machine Learning and Population Genetics, allowing to determine the number of clones that can be associated to selection forces.
- Giulio Caravagna, Timon Heide, Mark Williams, Luis Zapata, Dan Nichol, Kate Chkhaidze, Will Cross, George Cresswell, Benjamin Werner, Ahmet Acar, Louis Chesler, Chris Barnes, Guido Sanguinetti, Trevor Graham, Andrea Sottoriva. Subclonal reconstruction of tumors by using machine learning and population genetics. Nature Genetics 52, 898–907 (2020).
Subclonal deconvolution of read counts from multiple bulk sequencing biopsies, using a variational Bayesian approach.
- Giulio Caravagna, Timon Heide, Mark Williams, Luis Zapata, Dan Nichol, Kate Chkhaidze, Will Cross, George Cresswell, Benjamin Werner, Ahmet Acar, Louis Chesler, Chris Barnes, Guido Sanguinetti, Trevor Graham, Andrea Sottoriva. Subclonal reconstruction of tumors by using machine learning and population genetics. Nature Genetics 52, 898–907 (2020).
Univariate Binomial and Beta-Binomial mixture models for subclonal deconvolution of read counts from bulk assays. Differently from VIBER this package works with a single biopsy and a maximum-likelihood approach.
- Giulio Caravagna, Timon Heide, Mark Williams, Luis Zapata, Dan Nichol, Kate Chkhaidze, Will Cross, George Cresswell, Benjamin Werner, Ahmet Acar, Louis Chesler, Chris Barnes, Guido Sanguinetti, Trevor Graham, Andrea Sottoriva. Subclonal reconstruction of tumors by using machine learning and population genetics. Nature Genetics 52, 898–907 (2020).
A model to infer repeated evolution from a cohort of multi-region samples of multiple tumour patients, with functions to stratify the cohort and determine evolutionary subgroups of tumours that evolve with different patterns.
- Giulio Caravagna, Ylenia Giarratano, Daniele Ramazzoti, Ian Tomlinson, Trevor Graham, Guido Sanguinetti, Andrea Sottoriva. Detecting repeated cancer evolution from multi-region tumor sequencing data. Nature Methods 15, 707–714 (2018).
Clones trees from multi-region bulk sequencing data, built of Cancer Cell Fractions clusters computed by subclonal deconvolution algorithms.
- Giulio Caravagna, Ylenia Giarratano, Daniele Ramazzoti, Ian Tomlinson, Trevor Graham, Guido Sanguinetti, Andrea Sottoriva. Detecting repeated cancer evolution from multi-region tumor sequencing data. Nature Methods 15, 707–714 (2018).
Mutation trees from multi-region bulk or single-cell sequencing data, where the presence or absence of a somatic mutation, a Copy Number event, or any other event available in binary format.
- Giulio Caravagna, Ylenia Giarratano, Daniele Ramazzoti, Ian Tomlinson, Trevor Graham, Guido Sanguinetti, Andrea Sottoriva. Detecting repeated cancer evolution from multi-region tumor sequencing data. Nature Methods 15, 707–714 (2018).
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