ArticleGenome research2019
SiCloneFit: Bayesian inference of population structure, genotype, and phylogeny of tumor clones from single-cell genome sequencing data.
Article in Genome research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.
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63 citing papers in PubMed, 138 citations in OpenAlex.
- Canopy2: Tumor Phylogeny Inference by Bulk DNA and Single-Cell RNA Sequencing.Statistics in biosciences · 2026Article
- De Novo Detection of Clonal Structure and Evolution in Single-Cell and Spatial Transcriptomes.International journal of molecular sciences · 2025Article
- Cancer subclone detection based on DNA copy number in single-cell and spatial omic sequencing data.Nature methods · 2025Article
- DelSIEVE: cell phylogeny modeling of single nucleotide variants and deletions from single-cell DNA sequencing data.Genome biology · 2025Article
- Bayesian inference of fitness landscapes via tree-structured branching processes.Bioinformatics (Oxford, England) · 2025Article
- Somatic mutation phasing and haplotype extension using linked-reads in multiple myeloma.bioRxiv : the preprint server for biology · 2024Article
- A Probabilistic Approach to Estimate the Temporal Order of Pathway Mutations Accounting for Intra-Tumor Heterogeneity.Cancers · 2024Article
- Scuphr: A probabilistic framework for cell lineage tree reconstruction.PLoS computational biology · 2024Article
- scGAL: unmask tumor clonal substructure by jointly analyzing independent single-cell copy number and scRNA-seq data.BMC genomics · 2024Article
- Article
- A statistical learning method for simultaneous copy number estimation and subclone clustering with single-cell sequencing data.Genome research · 2024Article
- Analyzing somatic mutations by single-cell whole-genome sequencing.Nature protocols · 2024Review
- Assessing the merits: an opinion on the effectiveness of simulation techniques in tumor subclonal reconstruction.Bioinformatics advances · 2024Article
- Integrating SNVs and CNAs on a phylogenetic tree from single-cell DNA sequencing data.Genome research · 2023Article
- Quartets enable statistically consistent estimation of cell lineage trees under an unbiased error and missingness model.Algorithms for molecular biology : AMB · 2023Article
- ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model.Genome biology · 2023Article
- Phertilizer: Growing a clonal tree from ultra-low coverage single-cell DNA sequencing of tumors.PLoS computational biology · 2023Article
- Assessing the performance of methods for cell clustering from single-cell DNA sequencing data.PLoS computational biology · 2023Article
- COMPASS: joint copy number and mutation phylogeny reconstruction from amplicon single-cell sequencing data.Nature communications · 2023Article
- Phylogenetic inference from single-cell RNA-seq data.Scientific reports · 2023Article
3 more citing papers are in PubMed but not listed here.
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4 authors at 2 institutions in 1 country.
Funding
Abstract
Accumulation and selection of somatic mutations in a Darwinian framework result in intra-tumor heterogeneity (ITH) that poses significant challenges to the diagnosis and clinical therapy of cancer. Identification of the tumor cell populations (clones) and reconstruction of their evolutionary relationship can elucidate this heterogeneity. Recently developed single-cell DNA sequencing (SCS) technologies promise to resolve ITH to a single-cell level. However, technical errors in SCS data sets, including false-positives (FP) and false-negatives (FN) due to allelic dropout, and cell doublets, significantly complicate these tasks. Here, we propose a nonparametric Bayesian method that reconstructs the clonal populations as clusters of single cells, genotypes of each clone, and the evolutionary relationship between the clones. It employs a tree-structured Chinese restaurant process as the prior on the number and composition of clonal populations. The evolution of the clonal populations is modeled by a clonal phylogeny and a finite-site model of evolution to account for potential mutation recurrence and losses. We probabilistically account for FP and FN errors, and cell doublets are modeled by employing a Beta-binomial distribution. We develop a Gibbs sampling algorithm comprising partial reversible-jump and partial Metropolis-Hastings updates to explore the joint posterior space of all parameters. The performance of our method on synthetic and experimental data sets suggests that joint reconstruction of tumor clones and clonal phylogeny under a finite-site model of evolution leads to more accurate inferences. Our method is the first to enable this joint reconstruction in a fully Bayesian framework, thus providing measures of support of the inferences it makes.
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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.