ReviewAdvances in experimental medicine and biology2022
Computational Approaches for the Investigation of Intra-tumor Heterogeneity and Clonal Evolution from Bulk Sequencing Data in Precision Oncology Applications.
Review in Advances in experimental medicine and biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Clinical decisions in clonal hematopoiesis: a contemporary review for clinicians.Haematologica · 2026Review
- Resolving intra-tumor heterogeneity and clonal evolution of core-binding factor acute myeloid leukemia patients with single-cell resolution.Experimental hematology & oncology · 2025Article
- Personalizing DNA Cancer Vaccines.Journal of personalized medicine · 2025Review
- GenoPath: a pipeline to infer tumor clone composition, mutational history, and metastatic cell migration events from tumor DNA sequencing data.Frontiers in bioinformatics · 2025Article
- Molecular targets and strategies in the development of nucleic acid cancer vaccines: from shared to personalized antigens.Journal of biomedical science · 2024Review
Corrections and comments
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Authors and funding
1 author.
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Abstract
While the clonal model of cancer evolution was first proposed over 40 years ago, only recently next-generation sequencing has allowed a more precise and quantitative assessment of tumor clonal and subclonal landscape. Consequently, a plethora of computational approaches and tools have been developed to analyze this data with the goal of inferring the clonal landscape of a tumor and characterize its temporal or spatial evolution. This chapter introduces intra-tumor heterogeneity (ITH) in the context of precision oncology applications and provides an overview of the basic concepts, algorithms, and tools for the dissection, analysis, and visualization of ITH from bulk DNA sequencing.
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