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GenoPath: a pipeline to infer tumor clone composition, mutational history, and metastatic cell migration events from tumor DNA sequencing data.

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Frontiers in bioinformatics 2025 Vol.5() p. 1615834
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Tobin RM, Singh S, Kumar S, Miura S

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DNA sequencing technologies are widely used to study tumor evolution within a cancer patient.

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APA Tobin RM, Singh S, et al. (2025). GenoPath: a pipeline to infer tumor clone composition, mutational history, and metastatic cell migration events from tumor DNA sequencing data.. Frontiers in bioinformatics, 5, 1615834. https://doi.org/10.3389/fbinf.2025.1615834
MLA Tobin RM, et al.. "GenoPath: a pipeline to infer tumor clone composition, mutational history, and metastatic cell migration events from tumor DNA sequencing data.." Frontiers in bioinformatics, vol. 5, 2025, pp. 1615834.
PMID 40672519 ↗

Abstract

DNA sequencing technologies are widely used to study tumor evolution within a cancer patient. However, analyses require various computational methods, including those to infer clone sequences (genotypes of cancer cell populations), clone frequencies within each tumor sample, clone phylogeny, mutational tree, dynamics of mutational signatures, and metastatic cell migration events. Therefore, we developed GenoPath, a streamlined pipeline of existing tools to perform tumor evolution analysis. We also developed and added tools to visualize results to assist interpretation and derive biological insights. We have illustrated GenoPath's utility through a case study of tumor evolution using metastatic prostate cancer data. By reducing computational barriers, GenoPath broadens access to tumor evolution analysis. The software is available at https://github.com/SayakaMiura/GP.

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