Journal Article

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

Szczurek, Ewa, Valecha, Monica, Kuipers, Jack, Borgsmüller, Nico, Posada, David, Markowska, Magda, Kang, Senbai, Beerenwinkel, Niko

2025

Overview

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.

• Publisher: BioMed Central,Springer Nature B.V,BMC
• Subject: Acquisition bias correction / Animal Genetics and Genomics / Binomial distribution / Bioinformatics / Biomedical and Life Sciences / Cell phylogeny reconstruction / Deletions / DNA / DNA sequencing / Evolutionary Biology / genome / Genomes / Genotype & phenotype / Human Genetics / Humans / Life Sciences / Methodology / Microbial Genetics and Genomics / Mutation / Neoplasms - genetics / Phylogenetics / Phylogeny / Plant Genetics and Genomics / Polymorphism, Single Nucleotide / Sequence Analysis, DNA - methods / Sequence Deletion / Single nucleotide variants / Single-Cell Analysis - methods / Single-cell DNA sequencing / Software / Statistical phylogenetic models