Evidence map›Paper›PMID 41509334›Full record

ArticlebioRxiv : the preprint server for biology2025

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

Michael Bowman, Shreeya Gounder, Varsha Singh, Olga Shestova, Troy Robinson, Amy Zhang, Anushka Gandhi, Roopsha Bandopadhyay, Sheng F Cai, Ross L Levine and 3 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Michael BowmanDepartment of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Shreeya GounderDepartment of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Varsha SinghDepartment of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Olga ShestovaDivision of Hematology-Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Troy RobinsonHuman Oncology and Pathogenesis Program, Molecular Cancer Medicine Service, Memorial Sloan Kettering Cancer Center, New York, NY.
Amy ZhangDepartment of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Anushka GandhiDepartment of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Roopsha BandopadhyayDepartment of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Sheng F CaiHuman Oncology and Pathogenesis Program, Molecular Cancer Medicine Service, Memorial Sloan Kettering Cancer Center, New York, NY.
Ross L LevineHuman Oncology and Pathogenesis Program, Molecular Cancer Medicine Service, Memorial Sloan Kettering Cancer Center, New York, NY.
Saar I GillDivision of Hematology-Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Linde A MilesDepartment of Pediatrics, University of Cincinnati, Cincinnati, OH.
Robert L BowmanDepartment of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.ORCID 0000-0002-8294-8748

Funding

Interrogating oncogene-dependency and mutation order in FLT3 mutant AMLR00CA248460 · NCI · UNIVERSITY OF PENNSYLVANIA · PI BOWMAN, ROBERT LYLE · 2022 to 2024
$743k
Dissecting the role of clonal evolution in NPM1-mutant AMLR00CA252005 · NCI · CINCINNATI CHILDRENS HOSP MED CTR · PI MILES, LINDE A · 2022 to 2024
$669k
NCI NIH HHS R00 CA248460NCI NIH HHS R00 CA252005
6 · The paper itself

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.

Identifiers

PMID41509334
PMCPMC12776156

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.