Sc-TUSV-Ext: Single-Cell Clonal Lineage Inference from Single Nucleotide Variants, Copy Number Alterations, and Structural Variants

Clonal lineage inference ("tumor phylogenetics") has become a crucial tool for making sense of somatic evolution processes that underlie cancer development and are increasingly recognized as part of normal tissue growth and aging. The inference of clonal lineage trees from single-cell sequence data offers particular promise for revealing processes of somatic evolution in unprecedented detail. However, most such tools are based on fairly restrictive models of the types of mutation events observed in somatic evolution and of the processes by which they develop. The present work seeks to enhance the power and versatility of tools for single-cell lineage reconstruction by making more comprehensive use of the range of molecular variant types by which tumors evolve. We introduce Sc-TUSV-ext, an integer linear programming-based tumor phylogeny reconstruction method that, for the first time, integrates single nucleotide variants, copy number alterations, and structural variations into clonal lineage reconstruction from single-cell DNA sequencing data. We show on synthetic data that accounting for these variant types collectively leads to improved accuracy in clonal lineage reconstruction relative to prior methods that consider only subsets of the variant types. We further demonstrate the effectiveness of real data in resolving clonal evolution in the presence of multiple variant types, providing a path toward more comprehensive insight into how various forms of somatic mutability collectively shape tissue development.

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Publication Details

Journal
Journal of Computational Biology
Published
2025-03-06
DOI
https://doi.org/10.1089/cmb.2024.0613
Citations
2
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
0.94
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article

Sc-TUSV-Ext: Single-Cell Clonal Lineage Inference from Single Nucleotide Variants, Copy Number Alterations, and Structural Variants

Nishat Anjum Bristy, Russell Schwartz, Xuecong Fu
2 citations
Journal of Computational Biology
Cancer Genomics and Diagnostics
0.94
article

Sc-TUSV-Ext: Single-Cell Clonal Lineage Inference from Single Nucleotide Variants, Copy Number Alterations, and Structural Variants

Nishat Anjum Bristy, Russell Schwartz, Xuecong Fu
article en
2 citations

Abstract

Clonal lineage inference ("tumor phylogenetics") has become a crucial tool for making sense of somatic evolution processes that underlie cancer development and are increasingly recognized as part of normal tissue growth and aging. The inference of clonal lineage trees from single-cell sequence data offers particular promise for revealing processes of somatic evolution in unprecedented detail. However, most such tools are based on fairly restrictive models of the types of mutation events observed in somatic evolution and of the processes by which they develop. The present work seeks to enhance the power and versatility of tools for single-cell lineage reconstruction by making more comprehensive use of the range of molecular variant types by which tumors evolve. We introduce Sc-TUSV-ext, an integer linear programming-based tumor phylogeny reconstruction method that, for the first time, integrates single nucleotide variants, copy number alterations, and structural variations into clonal lineage reconstruction from single-cell DNA sequencing data. We show on synthetic data that accounting for these variant types collectively leads to improved accuracy in clonal lineage reconstruction relative to prior methods that consider only subsets of the variant types. We further demonstrate the effectiveness of real data in resolving clonal evolution in the presence of multiple variant types, providing a path toward more comprehensive insight into how various forms of somatic mutability collectively shape tissue development.

Journal of Computational BiologyVol. 32(8)
Carnegie Mellon University (US)
Openalex Percentile: Top 28%
Cancer Genomics and Diagnostics
0.94
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