scDNA: Single Cell DNA analysis software toolkit for subclonality discovery and assessment

Advances in single cell multi-omics technologies have allowed for investigation into genotype-immunophenotype relationships and dynamic clonal changes in cancer patient samples. These technologies provide rich insights into genetic profiling, drivers of disease progression, and subclonal dynamics. Increased adoption and throughput of these technologies, necessitate accessible computational tools for processing and analysis. Toward developing easy to use computational tools, we introduce the Single Cell DNA (scDNA) package that allows for rapid analysis of single-cell molecular profiling. Our platform aims to provide a diagnostic summary tool for sample quality control, representative subclonal architecture within a sample, demultiplexing functionality for multi-sample processing, copy number variation, and mutation trajectory analysis to identify order of subclonal mutation acquisition. We showcase a series of vignettes on hematopoiesis datasets for each aim that reflects recently deployed uses of scDNA. Additionally, we show scDNA provides a modular, user-friendly framework that readily feeds into other standard software pipelines.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2025-12-22
DOI
https://doi.org/10.64898/2025.12.19.694255
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
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article

scDNA: Single Cell DNA analysis software toolkit for subclonality discovery and assessment

Troy M. Robinson, Ross L. Levine, Linde A. Miles, Shreeya D. Gounder et al.
bioRxiv (Cold Spring Harbor Laboratory)
Cancer Genomics and Diagnostics
article

scDNA: Single Cell DNA analysis software toolkit for subclonality discovery and assessment

Troy M. Robinson, Ross L. Levine, Linde A. Miles, Shreeya D. Gounder, Olga Shestova, Sheng F. Cai, Varsha Singh, Michael Bowman
article en

Abstract

Advances in single cell multi-omics technologies have allowed for investigation into genotype-immunophenotype relationships and dynamic clonal changes in cancer patient samples. These technologies provide rich insights into genetic profiling, drivers of disease progression, and subclonal dynamics. Increased adoption and throughput of these technologies, necessitate accessible computational tools for processing and analysis. Toward developing easy to use computational tools, we introduce the Single Cell DNA (scDNA) package that allows for rapid analysis of single-cell molecular profiling. Our platform aims to provide a diagnostic summary tool for sample quality control, representative subclonal architecture within a sample, demultiplexing functionality for multi-sample processing, copy number variation, and mutation trajectory analysis to identify order of subclonal mutation acquisition. We showcase a series of vignettes on hematopoiesis datasets for each aim that reflects recently deployed uses of scDNA. Additionally, we show scDNA provides a modular, user-friendly framework that readily feeds into other standard software pipelines.

bioRxiv (Cold Spring Harbor Laboratory)
Cincinnati Children's Hospital Medical Center (US), Memorial Sloan Kettering Cancer Center (US), University of Cincinnati (US), University of Pennsylvania (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 35%
Cancer Genomics and Diagnostics
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scDNA: Single Cell DNA analysis software toolkit for subclonality discovery and assessment — Troy M. Robinson, Ross L. Levine, et al. · bioRxiv (Cold Spring Harbor Laboratory) (2025) | TGRS Research Map | TGRS