ArticleNature methods2016
Monovar: single-nucleotide variant detection in single cells.
Article in Nature methods, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 95 papers.
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Who cites it
95 citing papers in PubMed.
- Phylogenetic and phylodynamic approaches to understanding the evolution of non-small cell lung cancer using single-cell sequencing.Oncogene · 2026Article
- BioTester: an AI-driven automated testing framework for identifying potential quality risks in bioinformatics software.Briefings in bioinformatics · 2026Article
- Stepwise Protocol for Alternative Splicing Analysis in Single-Cell SMART-Seq2 RNA-Seq Data.Bio-protocol · 2026Article
- Decoding immunotherapy response through computational modeling.Nature communications · 2026Review
- A single-cell atlas of RNA alternative splicing in the glioma-immune ecosystem.Genome biology · 2025Article
- CluVar: clustering of variants using autoencoder for inferring cancer subclones from single cell RNA sequencing data.Briefings in bioinformatics · 2025Article
- SNPmanifold: detecting single-cell clonality and lineages from single-nucleotide variants using binomial variational autoencoder.Genome biology · 2025Article
- DelSIEVE: cell phylogeny modeling of single nucleotide variants and deletions from single-cell DNA sequencing data.Genome biology · 2025Article
- Differential performance of strategies for single-cell whole-genome amplification.Cell reports methods · 2025Article
- Review
- Inferring active mutational processes in cancer using single cell sequencing and evolutionary constraints.bioRxiv : the preprint server for biology · 2025Article
- Direct inference of haplotypes from sequencing data.Bioinformatics advances · 2025Article
- Scuphr: A probabilistic framework for cell lineage tree reconstruction.PLoS computational biology · 2024Article
- De novo detection of somatic mutations in high-throughput single-cell profiling data sets.Nature biotechnology · 2024Article
- Single-nucleotide variant calling in single-cell sequencing data with Monopogen.Nature biotechnology · 2024Article
- Interrogations of single-cell RNA splicing landscapes with SCASL define new cell identities with physiological relevance.Nature communications · 2024Article
- Computational immunogenomic approaches to predict response to cancer immunotherapies.Nature reviews. Clinical oncology · 2024Review
- Assessing the performance of methods for cell clustering from single-cell DNA sequencing data.PLoS computational biology · 2023Article
- Single-cell phylogenies reveal changes in the evolutionary rate within cancer and healthy tissues.Cell genomics · 2023Article
- Article
35 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Current variant callers are not suitable for single-cell DNA sequencing, as they do not account for allelic dropout, false-positive errors and coverage nonuniformity. We developed Monovar (https://bitbucket.org/hamimzafar/monovar), a statistical method for detecting and genotyping single-nucleotide variants in single-cell data. Monovar exhibited superior performance over standard algorithms on benchmarks and in identifying driver mutations and delineating clonal substructure in three different human tumor data sets.
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Registered trials
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.