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bioRxiv · 10.1101/2024.08.14.607069

PhyClone: Accurate Bayesian reconstruction of cancer phylogenies from bulk sequencing

Hurtado, E.·Bouchard-Cote, A.·Roth, A.
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Abstract

MotivationCancer is driven by somatic mutations that result in the expansion of genomically distinct sub-populations of cells called clones. Identifying the clonal composition of tumours and understanding the evolutionary relationships between clones is a crucial task in cancer genomics. Bulk DNA sequencing is commonly used for studying the clonal composition of tumours, but it is challenging to infer the genetic relationship between different clones due to the mixture of different cell populations. ResultsIn this work, we introduce a new probabilistic model called PhyClone that can infer clonal phylogenies from bulk sequencing data. We demonstrate the performance of PhyClone on simulated and real-world datasets and show that it outperforms previous methods in terms of accuracy and scalability. Availability and implementationSource code is available on Github at: https://github.com/Roth-Lab/PhyClone under the GPL v3.0 license. Contactaroth@bccrc.ca

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Hurtado, E., Bouchard-Cote, A., Roth, A.. 2024-08-17. PhyClone: Accurate Bayesian reconstruction of cancer phylogenies from bulk sequencing. https://doi.org/10.1101/2024.08.14.607069

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