ArticleNature communications2018
Single-cell mutation identification via phylogenetic inference.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.
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Who cites it
59 citing papers in PubMed.
- Computational approaches for multimodal lineage tracing.Nature reviews. Genetics · 2026Review
- Phylogenetic and phylodynamic approaches to understanding the evolution of non-small cell lung cancer using single-cell sequencing.Oncogene · 2026Article
- LAML-Pro: joint maximum likelihood inference of cell genotypes and cell lineage trees.Bioinformatics (Oxford, England) · 2026Article
- Phylogenetic tree inference from single-cell RNA sequencing data with SCITE-RNA.Genome biology · 2026Article
- Geospatial genetic evolution and phenotypic plasticity in triple-negative breast cancer.Genome medicine · 2026Article
- Single-cell genomic analysis of cancer cells from one treatment-naïve patient with metastatic prostate cancer.BMC genomic data · 2026Article
- LAML-Pro: Joint Maximum Likelihood Inference of Cell Genotypes and Cell Lineage Trees.bioRxiv : the preprint server for biology · 2026Article
- scSNViz: visualization and analysis of cell-specific expressed SNVs.Bioinformatics (Oxford, England) · 2026Article
- Canopy2: Tumor Phylogeny Inference by Bulk DNA and Single-Cell RNA Sequencing.Statistics in biosciences · 2026Article
- Clinical application of single-cell RNA sequencing in disease and therapy.Clinical and translational medicine · 2025Review
- DelSIEVE: cell phylogeny modeling of single nucleotide variants and deletions from single-cell DNA sequencing data.Genome biology · 2025Article
- Phylogenetic inference reveals clonal heterogeneity in circulating tumor cell clusters.Nature genetics · 2025Article
- CNRein: an evolution-aware deep reinforcement learning algorithm for single-cell DNA copy number calling.Genome biology · 2025Article
- Single-cell copy number calling and event history reconstruction.Bioinformatics (Oxford, England) · 2025Article
- Inferring active mutational processes in cancer using single cell sequencing and evolutionary constraints.bioRxiv : the preprint server for biology · 2025Article
- Joint inference of cell lineage and mitochondrial evolution from single-cell sequencing data.Bioinformatics (Oxford, England) · 2024Article
- Scuphr: A probabilistic framework for cell lineage tree reconstruction.PLoS computational biology · 2024Article
- Article
- Assessing the merits: an opinion on the effectiveness of simulation techniques in tumor subclonal reconstruction.Bioinformatics advances · 2024Article
- ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model.Genome biology · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Reconstructing the evolution of tumors is a key aspect towards the identification of appropriate cancer therapies. The task is challenging because tumors evolve as heterogeneous cell populations. Single-cell sequencing holds the promise of resolving the heterogeneity of tumors; however, it has its own challenges including elevated error rates, allelic drop-out, and uneven coverage. Here, we develop a new approach to mutation detection in individual tumor cells by leveraging the evolutionary relationship among cells. Our method, called SCIΦ, jointly calls mutations in individual cells and estimates the tumor phylogeny among these cells. Employing a Markov Chain Monte Carlo scheme enables us to reliably call mutations in each single cell even in experiments with high drop-out rates and missing data. We show that SCIΦ outperforms existing methods on simulated data and applied it to different real-world datasets, namely a whole exome breast cancer as well as a panel acute lymphoblastic leukemia dataset.
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