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Kang, S.* ; Borgsmüller, N.* ; Valecha, M.* ; Markowska, M.* ; Kuipers, J.* ; Beerenwinkel, N.* ; Posada, D.* ; Szczurek, E.

DelSIEVE: Cell phylogeny modeling of single nucleotide variants and deletions from single-cell DNA sequencing data.

Genome Biol. 26:255 (2025)
Verlagsversion Forschungsdaten DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
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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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter 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
Zeitschrift Genome Biology
Quellenangaben Band: 26, Heft: 1, Seiten: , Artikelnummer: 255 Supplement: ,
Verlag BioMed Central
Verlagsort Campus, 4 Crinan St, London N1 9xw, England
Begutachtungsstatus Peer reviewed
Institut(e) Institute of AI for Health (AIH)
Förderungen odowska-Curie Actions
H2020 Marie Sklstrok