ArticleMolecular biology and evolution2020
CellCoal: Coalescent Simulation of Single-Cell Sequencing Samples.
Article in Molecular biology and evolution, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Theoretical estimates on the expected number of mutations needed to reconstruct clonal lineage trees.Bioinformatics advances · 2026Article
- SISTEM: simulation of tumor evolution, metastasis, and DNA-seq data under genotype-driven selection.Bioinformatics (Oxford, England) · 2025Article
- A graph homomorphism approach for unraveling histories of metastatic cancers and viral outbreaks under evolutionary constraints.Nature communications · 2025Article
- DelSIEVE: cell phylogeny modeling of single nucleotide variants and deletions from single-cell DNA sequencing data.Genome biology · 2025Article
- CINner: Modeling and simulation of chromosomal instability in cancer at single-cell resolution.PLoS computational biology · 2025Article
- DICE: fast and accurate distance-based reconstruction of single-cell copy number phylogenies.Life science alliance · 2025Article
- CINner: modeling and simulation of chromosomal instability in cancer at single-cell resolution.bioRxiv : the preprint server for biology · 2024Article
- Article
- Assessing the merits: an opinion on the effectiveness of simulation techniques in tumor subclonal reconstruction.Bioinformatics advances · 2024Article
- Single-cell phylogenies reveal changes in the evolutionary rate within cancer and healthy tissues.Cell genomics · 2023Article
- CNAsim: improved simulation of single-cell copy number profiles and DNA-seq data from tumors.Bioinformatics (Oxford, England) · 2023Article
- Testing for Phylogenetic Signal in Single-Cell RNA-Seq Data.Journal of computational biology : a journal of computational molecular cell biology · 2023Article
- AlcoR: alignment-free simulation, mapping, and visualization of low-complexity regions in biological data.GigaScience · 2022Article
- A phylogenetic approach to inferring the order in which mutations arise during cancer progression.PLoS computational biology · 2022Article
- SIEVE: joint inference of single-nucleotide variants and cell phylogeny from single-cell DNA sequencing data.Genome biology · 2022Article
- J-SPACE: a Julia package for the simulation of spatial models of cancer evolution and of sequencing experiments.BMC bioinformatics · 2022Article
- SCSilicon: a tool for synthetic single-cell DNA sequencing data generation.BMC genomics · 2022Article
- CellPhy: accurate and fast probabilistic inference of single-cell phylogenies from scDNA-seq data.Genome biology · 2022Article
- Discrete coalescent trees.Journal of mathematical biology · 2021Article
- doubletD: detecting doublets in single-cell DNA sequencing data.Bioinformatics (Oxford, England) · 2021Article
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Abstract
Our capacity to study individual cells has enabled a new level of resolution for understanding complex biological systems such as multicellular organisms or microbial communities. Not surprisingly, several methods have been developed in recent years with a formidable potential to investigate the somatic evolution of single cells in both healthy and pathological tissues. However, single-cell sequencing data can be quite noisy due to different technical biases, so inferences resulting from these new methods need to be carefully contrasted. Here, I introduce CellCoal, a software tool for the coalescent simulation of single-cell sequencing genotypes. CellCoal simulates the history of single-cell samples obtained from somatic cell populations with different demographic histories and produces single-nucleotide variants under a variety of mutation models, sequencing read counts, and genotype likelihoods, considering allelic imbalance, allelic dropout, amplification, and sequencing errors, typical of this type of data. CellCoal is a flexible tool that can be used to understand the implications of different somatic evolutionary processes at the single-cell level, and to benchmark dedicated bioinformatic tools for the analysis of single-cell sequencing data. CellCoal is available at https://github.com/dapogon/cellcoal.
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