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DelSIEVE: Cell phylogeny modeling of single nucleotide variants and deletions from single-cell DNA sequencing data.
Genome Biol. 26:255 (2025)
With rapid advancements in single-cell DNA sequencing (scDNA-seq), various computational methods have been developed to study evolution and call variants on single-cell level. However, modeling deletions remains challenging because they affect total coverage in ways that are difficult to distinguish from technical artifacts. We present DelSIEVE, a statistical method that infers cell phylogeny and single-nucleotide variants, accounting for deletions, from scDNA-seq data. DelSIEVE distinguishes deletions from mutations and artifacts, detecting more evolutionary events than previous methods. Simulations show high performance, and application to cancer samples reveals varying amounts of deletions and double mutants in different tumors.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Acquisition Bias Correction ; Cell Phylogeny Reconstruction ; Colorectal Cancer ; Deletions ; Single Nucleotide Variants ; Single-cell Dna Sequencing ; Statistical Phylogenetic Models ; Triple Negative Breast Cancer; Copy-number; Clonal Evolution; Cancer; Mutation; Hallmarks; Trees; Simulation; Patterns; Sites
ISSN (print) / ISBN
1474-760X
e-ISSN
1465-6906
Journal
Genome Biology
Quellenangaben
Volume: 26,
Issue: 1,
Article Number: 255
Publisher
BioMed Central
Publishing Place
Campus, 4 Crinan St, London N1 9xw, England
Reviewing status
Peer reviewed
Institute(s)
Institute of AI for Health (AIH)
Grants
odowska-Curie Actions
H2020 Marie Sklstrok
H2020 Marie Sklstrok