DelSIEVE: cell phylogeny modeling of single nucleotide variants and deletions from single-cell DNA sequencing data
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.
Authors
- Monica Valecha (ORCID: https://orcid.org/0000-0001-9710-4129)
- Niko Beerenwinkel (ORCID: https://orcid.org/0000-0002-0573-6119)
- Ewa Szczurek (ORCID: https://orcid.org/0000-0002-1320-6695)
- Jack Kuipers (ORCID: https://orcid.org/0000-0001-5357-2705)
- David Posada (ORCID: https://orcid.org/0000-0003-1407-3406)
- Senbai Kang (ORCID: https://orcid.org/0000-0001-6696-3983)
- Nico Borgsmüller
- Magda Markowska (ORCID: https://orcid.org/0000-0002-0231-6397)
Institutions
- SIB Swiss Institute of Bioinformatics (CH)
- Medical University of Warsaw (PL)
- Helmholtz Zentrum München (DE)
- ETH Zurich (CH)
- Galicia Sur Biomedical Foundation (ES)
- Postgraduate School of Molecular Medicine (PL)
- Servicio Gallego de Salud (ES)
- University of Warsaw (PL)
- Universidade de Vigo (ES)
Publication Details
- Journal
- Genome biology
- Published
- 2025-08-25
- DOI
- https://doi.org/10.1186/s13059-025-03738-9
- Citations
- 2
- Primary Topic
- Cancer Genomics and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 1.87
Funders
- Ministerio de Ciencia e Innovación
- Xunta de Galicia
- H2020 Marie Skłodowska-Curie Actions
- FP7 Ideas: European Research Council