ArticlePLoS computational biology2014
Phylogenetic quantification of intra-tumour heterogeneity.
Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 97 papers.
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Who cites it
97 citing papers in PubMed.
- Theoretical estimates on the expected number of mutations needed to reconstruct clonal lineage trees.Bioinformatics advances · 2026Article
- CDKN2A homozygous deletions and TSC2 somatic mutations in metastatic pancreatic neuroendocrine tumors.NPJ precision oncology · 2025Article
- Detecting branching rate heterogeneity with tree balance statistics in lineage tracing trees.bioRxiv : the preprint server for biology · 2025Article
- Evidence of DNA methylation heterogeneity and epipolymorphism in kidney cancer tissue samples.Oncogene · 2025Article
- Single-cell copy number calling and event history reconstruction.Bioinformatics (Oxford, England) · 2025Article
- DICE: fast and accurate distance-based reconstruction of single-cell copy number phylogenies.Life science alliance · 2025Article
- Deconvolution and Phylogeny Inference of Diverse Variant Types Integrating Bulk DNA-seq with Single-cell RNA-seq.bioRxiv : the preprint server for biology · 2025Article
- Analysis of Shared Variants between Cancer Biospecimens.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025Article
- Cancer phylogenetic inference using copy number alterations detected from DNA sequencing data.Cancer pathogenesis and therapy · 2025Review
- Computational strategies in tumor phylogenetics: evaluating multimodal integration and methodological trade-offs across study designs.Bioinformatics advances · 2025Review
- Deconvolution and phylogeny inference of diverse variant types integrating bulk DNA-seq with single-cell RNA-seq.Bioinformatics advances · 2025Article
- Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics.Nature methods · 2024Article
- Improved allele-specific single-cell copy number estimation in low-coverage DNA-sequencing.Bioinformatics (Oxford, England) · 2024Article
- Inference of chromosome selection parameters and missegregation rate in cancer from DNA-sequencing data.Scientific reports · 2024Article
- NestedBD: Bayesian inference of phylogenetic trees from single-cell copy number profiles under a birth-death model.Algorithms for molecular biology : AMB · 2024Article
- scAbsolute: measuring single-cell ploidy and replication status.Genome biology · 2024Article
- A zero-agnostic model for copy number evolution in cancer.PLoS computational biology · 2023Article
- Refphase: Multi-sample phasing reveals haplotype-specific copy number heterogeneity.PLoS computational biology · 2023Article
- Single-cell methylation sequencing data reveal succinct metastatic migration histories and tumor progression models.Genome research · 2023Article
- CNETML: maximum likelihood inference of phylogeny from copy number profiles of multiple samples.Genome biology · 2023Article
37 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
Abstract
Intra-tumour genetic heterogeneity is the result of ongoing evolutionary change within each cancer. The expansion of genetically distinct sub-clonal populations may explain the emergence of drug resistance, and if so, would have prognostic and predictive utility. However, methods for objectively quantifying tumour heterogeneity have been missing and are particularly difficult to establish in cancers where predominant copy number variation prevents accurate phylogenetic reconstruction owing to horizontal dependencies caused by long and cascading genomic rearrangements. To address these challenges, we present MEDICC, a method for phylogenetic reconstruction and heterogeneity quantification based on a Minimum Event Distance for Intra-tumour Copy-number Comparisons. Using a transducer-based pairwise comparison function, we determine optimal phasing of major and minor alleles, as well as evolutionary distances between samples, and are able to reconstruct ancestral genomes. Rigorous simulations and an extensive clinical study show the power of our method, which outperforms state-of-the-art competitors in reconstruction accuracy, and additionally allows unbiased numerical quantification of tumour heterogeneity. Accurate quantification and evolutionary inference are essential to understand the functional consequences of tumour heterogeneity. The MEDICC algorithms are independent of the experimental techniques used and are applicable to both next-generation sequencing and array CGH data.
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