ArticleNature biotechnology2020
A community effort to create standards for evaluating tumor subclonal reconstruction.
Article in Nature biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- Accurate detection of tumor clonality and ongoing expansion mode from genomic data.bioRxiv : the preprint server for biology · 2026Article
- Decoding immunotherapy response through computational modeling.Nature communications · 2026Review
- Metapipeline-DNA: A comprehensive germline and somatic genomics Nextflow pipeline.Cell reports methods · 2026Article
- In silico generation of synthetic cancer genomes using generative AI.Cell genomics · 2025Article
- Acquired resistance in cancer: towards targeted therapeutic strategies.Nature reviews. Cancer · 2025Review
- The Germline and Somatic Origins of Prostate Cancer Heterogeneity.Cancer discovery · 2025Article
- Crowd-sourced benchmarking of single-sample tumor subclonal reconstruction.Nature biotechnology · 2025Article
- Orchard: Building large cancer phylogenies using stochastic combinatorial search.PLoS computational biology · 2024Article
- Oncotree2vec - a method for embedding and clustering of tumor mutation trees.Bioinformatics (Oxford, England) · 2024Article
- Joint inference of cell lineage and mitochondrial evolution from single-cell sequencing data.Bioinformatics (Oxford, England) · 2024Article
- The genomic and evolutionary landscapes of anaplastic thyroid carcinoma.Cell reports · 2024Article
- scAbsolute: measuring single-cell ploidy and replication status.Genome biology · 2024Article
- Article
- NFTest: automated testing of Nextflow pipelines.Bioinformatics (Oxford, England) · 2024Article
- Assessing the merits: an opinion on the effectiveness of simulation techniques in tumor subclonal reconstruction.Bioinformatics advances · 2024Article
- Integrated Genomic and Transcriptomic Analysis Improves Disease Classification and Risk Stratification of MDS with Ring Sideroblasts.Clinical cancer research : an official journal of the American Association for Cancer Research · 2023Article
- Cancer origin tracing and timing in two high-risk prostate cancers using multisample whole genome analysis: prospects for personalized medicine.Genome medicine · 2023Article
- PrecisionFDA Truth Challenge V2: Calling variants from short and long reads in difficult-to-map regions.Cell genomics · 2022Article
- Reconstructing Complex Cancer Evolutionary Histories from Multiple Bulk DNA Samples Using Pairtree.Blood cancer discovery · 2022Article
- Computational analysis of cancer genome sequencing data.Nature reviews. Genetics · 2022Review
Corrections and comments
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Authors and funding
33 authors.
Funding
Abstract
Tumor DNA sequencing data can be interpreted by computational methods that analyze genomic heterogeneity to infer evolutionary dynamics. A growing number of studies have used these approaches to link cancer evolution with clinical progression and response to therapy. Although the inference of tumor phylogenies is rapidly becoming standard practice in cancer genome analyses, standards for evaluating them are lacking. To address this need, we systematically assess methods for reconstructing tumor subclonality. First, we elucidate the main algorithmic problems in subclonal reconstruction and develop quantitative metrics for evaluating them. Then we simulate realistic tumor genomes that harbor all known clonal and subclonal mutation types and processes. Finally, we benchmark 580 tumor reconstructions, varying tumor read depth, tumor type and somatic variant detection. Our analysis provides a baseline for the establishment of gold-standard methods to analyze tumor heterogeneity.
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