{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T13:18:01Z","timestamp":1778764681841,"version":"3.51.4"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"Supplement_1","license":[{"start":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T00:00:00Z","timestamp":1656288000000},"content-version":"vor","delay-in-days":3,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["IIS-1812822"],"award-info":[{"award-number":["IIS-1812822"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["IIS-2106837"],"award-info":[{"award-number":["IIS-2106837"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,6,24]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>Single-nucleotide variants (SNVs) are the most common variations in the human genome. Recently developed methods for SNV detection from single-cell DNA sequencing data, such as SCI\u03a6 and scVILP, leverage the evolutionary history of the cells to overcome the technical errors associated with single-cell sequencing protocols. Despite being accurate, these methods are not scalable to the extensive genomic breadth of single-cell whole-genome (scWGS) and whole-exome sequencing (scWES) data.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Here, we report on a new scalable method, Phylovar, which extends the phylogeny-guided variant calling approach to sequencing datasets containing millions of loci. Through benchmarking on simulated datasets under different settings, we show that, Phylovar outperforms SCI\u03a6 in terms of running time while being more accurate than Monovar (which is not phylogeny-aware) in terms of SNV detection. Furthermore, we applied Phylovar to two real biological datasets: an scWES triple-negative breast cancer data consisting of 32 cells and 3375 loci as well as an scWGS data of neuron cells from a normal human brain containing 16 cells and approximately 2.5 million loci. For the cancer data, Phylovar detected somatic SNVs with high or moderate functional impact that were also supported by bulk sequencing dataset and for the neuron dataset, Phylovar identified 5745 SNVs with non-synonymous effects some of which were associated with neurodegenerative diseases.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>Phylovar is implemented in Python and is publicly available at https:\/\/github.com\/NakhlehLab\/Phylovar.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac254","type":"journal-article","created":{"date-parts":[[2022,4,14]],"date-time":"2022-04-14T11:10:15Z","timestamp":1649934615000},"page":"i195-i202","source":"Crossref","is-referenced-by-count":10,"title":["Phylovar: toward scalable phylogeny-aware inference of single-nucleotide variations from single-cell DNA sequencing data"],"prefix":"10.1093","volume":"38","author":[{"given":"Mohammadamin","family":"Edrisi","sequence":"first","affiliation":[{"name":"Department of Computer Science, Rice University , Houston, TX 77005, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Monica V","family":"Valecha","sequence":"additional","affiliation":[{"name":"CINBIO, Universidade de Vigo , Vigo 36310, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sunkara B V","family":"Chowdary","sequence":"additional","affiliation":[{"name":"Department of Computer Science & Engineering, Indian Institute of Technology Kanpur , Kanpur 208016, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sergio","family":"Robledo","sequence":"additional","affiliation":[{"name":"University of Houston , Houston, TX 77204, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huw A","family":"Ogilvie","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Rice University , Houston, TX 77005, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Posada","sequence":"additional","affiliation":[{"name":"CINBIO, Universidade de Vigo , Vigo 36310, Spain"},{"name":"Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO , Vigo, Spain"},{"name":"Department of Biochemistry, Genetics, and Immunology, Universidade de Vigo , Vigo 36310, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hamim","family":"Zafar","sequence":"additional","affiliation":[{"name":"Department of Computer Science & Engineering, Indian Institute of Technology Kanpur , Kanpur 208016, India"},{"name":"Department of Biological Sciences & Bioengineering, Institute of Technology Kanpur , Kanpur 208016, India"},{"name":"Mehta Family Centre for Engineering in Medicine, Indian Institute of Technology Kanpur , Kanpur 208016, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luay","family":"Nakhleh","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Rice University , Houston, TX 77005, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2022,6,27]]},"reference":[{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"80","DOI":"10.4161\/fly.19695","article-title":"A program for annotating and predicting the effects of single nucleotide polymorphisms, snpeff: snps in the genome of drosophila melanogaster strain w1118; iso-2; iso-3","volume":"6","author":"Cingolani","year":"2012","journal-title":"Fly (Austin)"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"5261","DOI":"10.1073\/pnas.082089499","article-title":"Comprehensive human genome amplification using multiple displacement amplification","volume":"99","author":"Dean","year":"2002","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1186\/s13059-015-0602-8","article-title":"PhyloWGS: reconstructing subclonal composition and evolution from whole-genome sequencing of tumors","volume":"16","author":"Deshwar","year":"2015","journal-title":"Genome Biol"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1038\/nmeth.4227","article-title":"Accurate identification of single-nucleotide variants in whole-genome-amplified single cells","volume":"14","author":"Dong","year":"2017","journal-title":"Nat. Methods"},{"key":"2023041407571160600_","first-page":"22:1","author":"Edrisi","year":"2019"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/0025-5564(76)90035-3","article-title":"A mathematical foundation for the analysis of cladistic character compatibility","volume":"29","author":"Estabrook","year":"1976","journal-title":"Math. Biosci"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.neuron.2014.12.028","article-title":"Cell lineage analysis in human brain using endogenous retroelements","volume":"85","author":"Evrony","year":"2015","journal-title":"Neuron"},{"key":"2023041407571160600_","first-page":"203","volume-title":"The Perfect Phylogeny Problem","author":"Fern\u00e1ndez-Baca","year":"2001"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1002\/net.3230210104","article-title":"Efficient algorithm for inferring evolutionary trees","volume":"21","author":"Gusfield","year":"1991","journal-title":"Networks"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511574931","volume-title":"Algorithms on Strings, Trees and Sequences","author":"Gusfield","year":"1997"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1038\/s41586-020-2649-2","article-title":"Array programming with NumPy","volume":"585","author":"Harris","year":"2020","journal-title":"Nature"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1186\/s13059-016-0936-x","article-title":"Tree inference for single-cell data","volume":"17","author":"Jahn","year":"2016","journal-title":"Genome Biol"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"1419","DOI":"10.1038\/s12276-020-00499-2","article-title":"Single-cell sequencing techniques from individual to multiomics analyses","volume":"52","author":"Kashima","year":"2020","journal-title":"Exp. Mol. Med"},{"key":"2023041407571160600_","author":"Kuipers","year":"2020"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1186\/s13059-020-1926-6","article-title":"Eleven grand challenges in single-cell data science","volume":"21","author":"L\u00e4hnemann","year":"2020","journal-title":"Genome Biol"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"456","DOI":"10.1016\/j.ccell.2020.03.008","article-title":"Advancing cancer research and medicine with Single-cell genomics","volume":"37","author":"Lim","year":"2020","journal-title":"Cancer Cell"},{"key":"2023041407571160600_","author":"Markowska","year":"2021"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1007\/978-3-642-69024-2_34","volume-title":"Numerical Taxonomy","author":"Meacham","year":"1983","edition":"ed."},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1186\/s13059-014-0452-9","article-title":"Cancer genomics: one cell at a time","volume":"15","author":"Navin","year":"2014","journal-title":"Genome Biol"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1038\/nature09807","article-title":"Tumour evolution inferred by single-cell sequencing","volume":"472","author":"Navin","year":"2011","journal-title":"Nature"},{"key":"2023041407571160600_","first-page":"406","article-title":"The neighbor-joining method: a new method for reconstructing phylogenetic trees","volume":"4","author":"Saitou","year":"1987","journal-title":"Mol. Biol. Evol"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198509424.001.0001","volume-title":"Phylogenetics","author":"Semple","year":"2003"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"5144","DOI":"10.1038\/s41467-018-07627-7","article-title":"Single-cell mutation identification via phylogenetic inference","volume":"9","author":"Singer","year":"2018","journal-title":"Nat. Commun"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"1965","DOI":"10.1038\/nprot.2006.326","article-title":"Whole-genome multiple displacement amplification from single cells","volume":"1","author":"Spits","year":"2006","journal-title":"Nat. Protoc"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"lqab019","DOI":"10.1093\/nargab\/lqab019","article-title":"Sequencing error profiles of illumina sequencing instruments","volume":"3","author":"Stoler","year":"2021","journal-title":"NAR Genom. Bioinform"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1038\/nmeth.1315","article-title":"mRNA-Seq whole-transcriptome analysis of a single cell","volume":"6","author":"Tang","year":"2009","journal-title":"Nat. Methods"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1186\/s13578-019-0314-y","article-title":"The single-cell sequencing: new developments and medical applications","volume":"9","author":"Tang","year":"2019","journal-title":"Cell Biosci"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1038\/s41592-019-0686-2","article-title":"SciPy 1.0: fundamental algorithms for scientific computing in python","volume":"17","author":"Virtanen","year":"2020","journal-title":"Nat. Methods"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"598","DOI":"10.1016\/j.molcel.2015.05.005","article-title":"Advances and applications of single-cell sequencing technologies","volume":"58","author":"Wang","year":"2015","journal-title":"Mol. Cell"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1038\/nature13600","article-title":"Clonal evolution in breast cancer revealed by single nucleus genome sequencing","volume":"512","author":"Wang","year":"2014","journal-title":"Nature"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"904","DOI":"10.1038\/s41436-018-0274-3","article-title":"Frequency and signature of somatic variants in 1461 human brain exomes","volume":"21","author":"Wei","year":"2019","journal-title":"Genet. Med"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1038\/nmeth.3835","article-title":"Monovar: single-nucleotide variant detection in single cells","volume":"13","author":"Zafar","year":"2016","journal-title":"Nat. Methods"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1186\/s13059-017-1311-2","article-title":"SiFit: inferring tumor trees from single-cell sequencing data under finite-sites models","volume":"18","author":"Zafar","year":"2017","journal-title":"Genome Biol"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.coisb.2017.11.008","article-title":"Computational approaches for inferring tumor evolution from single-cell genomic data","volume":"7","author":"Zafar","year":"2018","journal-title":"Curr. Opin. Syst. Biol"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"1847","DOI":"10.1101\/gr.243121.118","article-title":"SiCloneFit: Bayesian inference of population structure, genotype, and phylogeny of tumor clones from single-cell genome sequencing data","volume":"29","author":"Zafar","year":"2019","journal-title":"Genome Res"},{"key":"2023041407571160600_","doi-asserted-by":"crossref","first-page":"1622","DOI":"10.1126\/science.1229164","article-title":"Genome-wide detection of single-nucleotide and copy-number variations of a single human cell","volume":"338","author":"Zong","year":"2012","journal-title":"Science"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/38\/Supplement_1\/i195\/49887284\/btac254.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/38\/Supplement_1\/i195\/49887284\/btac254.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,22]],"date-time":"2024-09-22T06:55:47Z","timestamp":1726988147000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/38\/Supplement_1\/i195\/6617481"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,24]]},"references-count":36,"journal-issue":{"issue":"Supplement_1","published-print":{"date-parts":[[2022,6,24]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btac254","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2022,7,1]]},"published":{"date-parts":[[2022,6,24]]}}}