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

Abstract 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...

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Main Authors: Palash Sashittal, Haochen Zhang, Christine A. Iacobuzio-Donahue, Benjamin J. Raphael
Format: Article
Language:English
Published: BMC 2023-11-01
Series:Genome Biology
Subjects:
Online Access:https://doi.org/10.1186/s13059-023-03106-5
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author Palash Sashittal
Haochen Zhang
Christine A. Iacobuzio-Donahue
Benjamin J. Raphael
author_facet Palash Sashittal
Haochen Zhang
Christine A. Iacobuzio-Donahue
Benjamin J. Raphael
author_sort Palash Sashittal
collection DOAJ
description Abstract 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.
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spelling doaj.art-5435dde5ac3e4bb780badd7e110b055f2023-12-03T12:24:31ZengBMCGenome Biology1474-760X2023-11-0124112310.1186/s13059-023-03106-5ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss modelPalash Sashittal0Haochen Zhang1Christine A. Iacobuzio-Donahue2Benjamin J. Raphael3Department of Computer Science, Princeton UniversityGerstner Sloan Kettering Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer CenterHuman Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer CenterDepartment of Computer Science, Princeton UniversityAbstract 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.https://doi.org/10.1186/s13059-023-03106-5CancerIntra-tumor heterogeneityTumor phylogenySingle-cell DNA sequencingDollo model
spellingShingle Palash Sashittal
Haochen Zhang
Christine A. Iacobuzio-Donahue
Benjamin J. Raphael
ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model
Genome Biology
Cancer
Intra-tumor heterogeneity
Tumor phylogeny
Single-cell DNA sequencing
Dollo 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 Cancer
Intra-tumor heterogeneity
Tumor phylogeny
Single-cell DNA sequencing
Dollo model
url https://doi.org/10.1186/s13059-023-03106-5
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