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Updated: Sep 10, 2025

Detection of Copy Number Alterations Using Single Cell Sequencing
Published on: February 17, 2017
DelSIEVE: cell phylogeny modeling of single nucleotide variants and deletions from single-cell DNA sequencing data
Senbai Kang1, Nico Borgsmüller2,3, Monica Valecha4,5
1Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland.
Abstract:
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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