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ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model

A tumor contains a diverse collection of somatic mutations that reflect its past evolutionary history and that range in scale from single nucleotide variants (SNVs) to large-scale copy-number aberrations (CNAs). However, no current single-cell DNA sequencing (scDNA-seq) technology produces accurate...

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Autores principales: Sashittal, Palash, Zhang, Haochen, Iacobuzio-Donahue, Christine A., Raphael, Benjamin J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10688497/
https://www.ncbi.nlm.nih.gov/pubmed/38037115
http://dx.doi.org/10.1186/s13059-023-03106-5
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author Sashittal, Palash
Zhang, Haochen
Iacobuzio-Donahue, Christine A.
Raphael, Benjamin J.
author_facet Sashittal, Palash
Zhang, Haochen
Iacobuzio-Donahue, Christine A.
Raphael, Benjamin J.
author_sort Sashittal, Palash
collection PubMed
description A tumor contains a diverse collection of somatic mutations that reflect its past evolutionary history and that range in scale from single nucleotide variants (SNVs) to large-scale copy-number aberrations (CNAs). However, no current single-cell DNA sequencing (scDNA-seq) technology produces accurate measurements of both SNVs and CNAs, complicating the inference of tumor phylogenies. We introduce a new evolutionary model, the constrained k-Dollo model, that uses SNVs as phylogenetic markers but constrains losses of SNVs according to clusters of cells. We derive an algorithm, ConDoR, that infers phylogenies from targeted scDNA-seq data using this model. We demonstrate the advantages of ConDoR on simulated and real scDNA-seq data. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03106-5.
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spelling pubmed-106884972023-11-30 ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model Sashittal, Palash Zhang, Haochen Iacobuzio-Donahue, Christine A. Raphael, Benjamin J. Genome Biol Method A tumor contains a diverse collection of somatic mutations that reflect its past evolutionary history and that range in scale from single nucleotide variants (SNVs) to large-scale copy-number aberrations (CNAs). However, no current single-cell DNA sequencing (scDNA-seq) technology produces accurate measurements of both SNVs and CNAs, complicating the inference of tumor phylogenies. We introduce a new evolutionary model, the constrained k-Dollo model, that uses SNVs as phylogenetic markers but constrains losses of SNVs according to clusters of cells. We derive an algorithm, ConDoR, that infers phylogenies from targeted scDNA-seq data using this model. We demonstrate the advantages of ConDoR on simulated and real scDNA-seq data. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03106-5. BioMed Central 2023-11-30 /pmc/articles/PMC10688497/ /pubmed/38037115 http://dx.doi.org/10.1186/s13059-023-03106-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Method
Sashittal, Palash
Zhang, Haochen
Iacobuzio-Donahue, Christine A.
Raphael, Benjamin J.
ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model
title ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model
title_full ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model
title_fullStr ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model
title_full_unstemmed ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model
title_short ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model
title_sort condor: tumor phylogeny inference with a copy-number constrained mutation loss model
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10688497/
https://www.ncbi.nlm.nih.gov/pubmed/38037115
http://dx.doi.org/10.1186/s13059-023-03106-5
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