R and Python packages.

As a lab, we maintain the following tools.

All our code is hosted at the CDSLab GitHub page.

Rcongas - Genotyping CNA on scRNAseq data (R interface)

Interface to the models implemented in the congas Python package. Functions for data preprocessing, visualisation and inference.

congas - Genotyping CNA on scRNAseq data (models implementation)

Python models written in the PPL Pyro, which implement for Copy Number Alternation (CNA) genotyping from single-cell RNA sequencing datasets.

mobster - Mode-based tumour subclonal deconvolution

Tumour subclonal deconvolution from whole-genome DNA sequencing, exploiting Machine Learning and Population Genetics.

REVOLVER - Repeated evolution in cancer

A model to computed repeated evolutionary trajectories from a cohort of multi-region samples of multiple tumour patients, stratify the cohort and determine evolutionary subgroups.

CNAqc - Copy Number Quality Check

The Copy Number Alterations quality check package to assess the concordance between copy number segments and somatic mutations, using peak detection metrics and Cancer Cell Fractions estimation.

VIBER - Multivariate mixture models for read counts deconvolution

Variational multivariate Binomial mixtures for subclonal deconvolution of read counts from multiple bulk sequencing biopsies.

BMix - Univariate mixture models for read counts deconvolution

Univariate Binomial and Beta-Binomial mixture models for subclonal deconvolution of read counts from one bulk sequencing biopsy.

ctree - Cancer Clone trees

Clones trees from multi-region bulk sequencing data, built of Cancer Cell Fractions (CCFs) clusters computed by tumour subclonal deconvolution algorithms (MOBSTER etc.).

mtree - Cancer mutation trees

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 is available in binary format.

TINC - Tumor in normal contamination

A method to determine the contamination of a tumour sample by normal cells, which can be used to QC tumour-normal samples.

evoverse.datasets - Data package

Input datasets and computation results from a number of packages that we have developed.