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ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model
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ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model
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Journal Article
ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model
2023
Overview
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.
Publisher
BioMed Central,Springer Nature B.V,BMC
Subject
/ Animal Genetics and Genomics
/ Animals
/ Biomedical and Life Sciences
/ Cancer
/ Cloning
/ DNA
/ genome
/ Genomes
/ Humans
/ Method
/ Microbial Genetics and Genomics
/ Mutation
/ Tumors
