{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T04:43:10Z","timestamp":1783572190189,"version":"3.55.0"},"reference-count":30,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2024,6,3]],"date-time":"2024-06-03T00:00:00Z","timestamp":1717372800000},"content-version":"vor","delay-in-days":11,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000060","name":"National Institute of Allergy and Infectious Diseases","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000060","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U19AI082724"],"award-info":[{"award-number":["U19AI082724"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U19AI109946"],"award-info":[{"award-number":["U19AI109946"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U19AI057266"],"award-info":[{"award-number":["U19AI057266"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NIAID Centers of Excellence for Influenza Research and Surveillance","award":["HHSN272201400005C"],"award-info":[{"award-number":["HHSN272201400005C"]}]},{"name":"NIAID Centers of Excellence for Influenza Research and Response","award":["75N93019R00028"],"award-info":[{"award-number":["75N93019R00028"]}]},{"name":"NIAID Collaborative Influenza Vaccine Innovation Centers","award":["75N93019C00051"],"award-info":[{"award-number":["75N93019C00051"]}]},{"name":"NIAID Centers of Excellence for Influenza Research and Surveillance","award":["HHSN272201400008C"],"award-info":[{"award-number":["HHSN272201400008C"]}]},{"name":"NIAID Centers of Excellence for Influenza Research and Response","award":["75N93021C00014"],"award-info":[{"award-number":["75N93021C00014"]}]},{"name":"CIHR Banting Postdoctoral Fellowship","award":["BPF-186528"],"award-info":[{"award-number":["BPF-186528"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,5,23]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Cell hashing, a nucleotide barcode-based method that allows users to pool multiple samples and demultiplex in downstream analysis, has gained widespread popularity in single-cell sequencing due to its compatibility, simplicity, and cost-effectiveness. Despite these advantages, the performance of this method remains unsatisfactory under certain circumstances, especially in experiments that have imbalanced sample sizes or use many hashtag antibodies. Here, we introduce a hybrid demultiplexing strategy that increases accuracy and cell recovery in multi-sample single-cell experiments. This approach correlates the results of cell hashing and genetic variant clustering, enabling precise and efficient cell identity determination without additional experimental costs or efforts. In addition, we developed HTOreader, a demultiplexing tool for cell hashing that improves the accuracy of cut-off calling by avoiding the dominance of negative signals in experiments with many hashtags or imbalanced sample sizes. When compared to existing methods using real-world datasets, this hybrid approach and HTOreader consistently generate reliable results with increased accuracy and cell recovery.<\/jats:p>","DOI":"10.1093\/bib\/bbae254","type":"journal-article","created":{"date-parts":[[2024,6,3]],"date-time":"2024-06-03T16:45:16Z","timestamp":1717433116000},"source":"Crossref","is-referenced-by-count":10,"title":["A hybrid demultiplexing strategy that improves performance and robustness of cell hashing"],"prefix":"10.1093","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8828-5199","authenticated-orcid":false,"given":"Lei","family":"Li","sequence":"first","affiliation":[{"name":"Gale and Ira Drukier Institute for Children\u2019s Health, Weill Cornell Medicine , 413 E. 69th Street, New York, NY 10021 , United States"},{"name":"Center for Applied Bioinformatics, St. Jude Children\u2019s Research Hospital , 262 Danny Thomas Place, Memphis, TN 38105 , United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiayi","family":"Sun","sequence":"additional","affiliation":[{"name":"Gale and Ira Drukier Institute for Children\u2019s Health, Weill Cornell Medicine , 413 E. 69th Street, New York, NY 10021 , United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanbin","family":"Fu","sequence":"additional","affiliation":[{"name":"Gale and Ira Drukier Institute for Children\u2019s Health, Weill Cornell Medicine , 413 E. 69th Street, New York, NY 10021 , United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siriruk","family":"Changrob","sequence":"additional","affiliation":[{"name":"Gale and Ira Drukier Institute for Children\u2019s Health, Weill Cornell Medicine , 413 E. 69th Street, New York, NY 10021 , United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joshua J C","family":"McGrath","sequence":"additional","affiliation":[{"name":"Gale and Ira Drukier Institute for Children\u2019s Health, Weill Cornell Medicine , 413 E. 69th Street, New York, NY 10021 , United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3537-1245","authenticated-orcid":false,"given":"Patrick C","family":"Wilson","sequence":"additional","affiliation":[{"name":"Gale and Ira Drukier Institute for Children\u2019s Health, Weill Cornell Medicine , 413 E. 69th Street, New York, NY 10021 , United States"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,6,3]]},"reference":[{"key":"2024060308155337100_ref1","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":"2024060308155337100_ref2","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1038\/nprot.2017.149","article-title":"Exponential scaling of single-cell RNA-seq in the past decade","volume":"13","author":"Svensson","year":"2018","journal-title":"Nat Protoc"},{"key":"2024060308155337100_ref3","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1038\/s41576-019-0093-7","article-title":"Integrative single-cell analysis","volume":"20","author":"Stuart","year":"2019","journal-title":"Nat Rev Genet"},{"key":"2024060308155337100_ref4","doi-asserted-by":"crossref","first-page":"1096","DOI":"10.1038\/nmeth.2639","article-title":"Smart-seq2 for sensitive full-length transcriptome profiling in single cells","volume":"10","author":"Picelli","year":"2013","journal-title":"Nat Methods"},{"key":"2024060308155337100_ref5","doi-asserted-by":"crossref","first-page":"1187","DOI":"10.1016\/j.cell.2015.04.044","article-title":"Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells","volume":"161","author":"Klein","year":"2015","journal-title":"Cell"},{"key":"2024060308155337100_ref6","doi-asserted-by":"crossref","first-page":"1202","DOI":"10.1016\/j.cell.2015.05.002","article-title":"Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets","volume":"161","author":"Macosko","year":"2015","journal-title":"Cell"},{"key":"2024060308155337100_ref7","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1126\/science.aam8940","article-title":"Comprehensive single-cell transcriptional profiling of a multicellular organism","volume":"357","author":"Cao","year":"2017","journal-title":"Science"},{"key":"2024060308155337100_ref8","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1186\/s13059-018-1603-1","article-title":"Cell hashing with barcoded antibodies enables multiplexing and doublet detection for single cell genomics","volume":"19","author":"Stoeckius","year":"2018","journal-title":"Genome Biol"},{"key":"2024060308155337100_ref9","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1038\/nbt.4042","article-title":"Multiplexed droplet single-cell RNA-sequencing using natural genetic variation","volume":"36","author":"Kang","year":"2018","journal-title":"Nat Biotechnol"},{"key":"2024060308155337100_ref10","doi-asserted-by":"crossref","first-page":"615","DOI":"10.1038\/s41592-020-0820-1","article-title":"Souporcell: robust clustering of single-cell RNA-seq data by genotype without reference genotypes","volume":"17","author":"Heaton","year":"2020","journal-title":"Nat Methods"},{"key":"2024060308155337100_ref11","doi-asserted-by":"crossref","first-page":"910","DOI":"10.1126\/science.aab1601","article-title":"Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing","volume":"348","author":"Cusanovich","year":"2015","journal-title":"Science"},{"key":"2024060308155337100_ref12","doi-asserted-by":"crossref","first-page":"466","DOI":"10.1007\/s00018-022-04482-0","article-title":"Sample-multiplexing approaches for single-cell sequencing","volume":"79","author":"Zhang","year":"2022","journal-title":"Cell Mol Life Sci"},{"key":"2024060308155337100_ref13","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1038\/s41592-019-0433-8","article-title":"MULTI-seq: sample multiplexing for single-cell RNA sequencing using lipid-tagged indices","volume":"16","author":"McGinnis","year":"2019","journal-title":"Nat Methods"},{"key":"2024060308155337100_ref14","doi-asserted-by":"crossref","first-page":"e10060","DOI":"10.15252\/msb.202010060","article-title":"CASB: a concanavalin A-based sample barcoding strategy for single-cell sequencing","volume":"17","author":"Fang","year":"2021","journal-title":"Mol Syst Biol"},{"key":"2024060308155337100_ref15","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1038\/s41587-019-0372-z","article-title":"Highly multiplexed single-cell RNA-seq by DNA oligonucleotide tagging of cellular proteins","volume":"38","author":"Gehring","year":"2020","journal-title":"Nat Biotechnol"},{"key":"2024060308155337100_ref16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-019-1852-7","article-title":"Genotype-free demultiplexing of pooled single-cell RNA-seq","volume":"20","author":"Xu","year":"2019","journal-title":"Genome Biol"},{"key":"2024060308155337100_ref17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-019-1865-2","article-title":"Vireo: Bayesian demultiplexing of pooled single-cell RNA-seq data without genotype reference","volume":"20","author":"Huang","year":"2019","journal-title":"Genome Biol"},{"key":"2024060308155337100_ref18","doi-asserted-by":"crossref","first-page":"eaav2249","DOI":"10.1126\/sciadv.aav2249","article-title":"Multiplexed single-cell RNA-seq via transient barcoding for simultaneous expression profiling of various drug perturbations","volume":"5","author":"Shin","year":"2019","journal-title":"Sci Adv"},{"key":"2024060308155337100_ref19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-019-1748-6","article-title":"BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single-cell analysis","volume":"20","author":"Uzbas","year":"2019","journal-title":"Genome Biol"},{"key":"2024060308155337100_ref20","doi-asserted-by":"crossref","first-page":"lqad086","DOI":"10.1093\/nargab\/lqad086","article-title":"Benchmarking single-cell hashtag oligo demultiplexing methods","volume":"5","author":"Howitt","year":"2023","journal-title":"NAR Genom Bioinform"},{"key":"2024060308155337100_ref21","doi-asserted-by":"crossref","first-page":"865","DOI":"10.1038\/nmeth.4380","article-title":"Simultaneous epitope and transcriptome measurement in single cells","volume":"14","author":"Stoeckius","year":"2017","journal-title":"Nat Methods"},{"key":"2024060308155337100_ref22","doi-asserted-by":"crossref","first-page":"3573","DOI":"10.1016\/j.cell.2021.04.048","article-title":"Integrated analysis of multimodal single-cell data","volume":"184","author":"Hao","year":"2021","journal-title":"Cell"},{"key":"2024060308155337100_ref23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-020-02084-2","article-title":"GMM-Demux: sample demultiplexing, multiplet detection, experiment planning, and novel cell-type verification in single cell sequencing","volume":"21","author":"Xin","year":"2020","journal-title":"Genome Biol"},{"key":"2024060308155337100_ref24","doi-asserted-by":"crossref","first-page":"2791","DOI":"10.1093\/bioinformatics\/btac213","article-title":"BFF and cellhashR: analysis tools for accurate demultiplexing of cell hashing data","volume":"38","author":"Boggy","year":"2022","journal-title":"Bioinformatics"},{"key":"2024060308155337100_ref25","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1186\/s13059-019-1662-y","article-title":"EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data","volume":"20","author":"Lun","year":"2019","journal-title":"Genome Biol"},{"key":"2024060308155337100_ref26","doi-asserted-by":"crossref","first-page":"1290","DOI":"10.1016\/j.immuni.2021.05.001","article-title":"Profiling B cell immunodominance after SARS-CoV-2 infection reveals antibody evolution to non-neutralizing viral targets","volume":"54","author":"Dugan","year":"2021","journal-title":"Immunity"},{"key":"2024060308155337100_ref27","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1111\/j.2517-6161.1982.tb01195.x","article-title":"The statistical analysis of compositional data","volume":"44","author":"Aitchison","year":"1982","journal-title":"J R Stat Soc Series B Stat Methodology"},{"key":"2024060308155337100_ref28","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1038\/nmeth.3734","article-title":"Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis","volume":"13","author":"Fan","year":"2016","journal-title":"Nat Methods"},{"key":"2024060308155337100_ref29","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1038\/nmeth.2967","article-title":"Bayesian approach to single-cell differential expression analysis","volume":"11","author":"Kharchenko","year":"2014","journal-title":"Nat Methods"},{"key":"2024060308155337100_ref30","article-title":"FlexMix: a general framework for finite mixture models and latent glass regression in R","volume-title":"Journal of Statistical Software","author":"Leisch","year":"2004"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/25\/4\/bbae254\/58056582\/bbae254.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/25\/4\/bbae254\/58056582\/bbae254.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,3]],"date-time":"2024-06-03T16:45:48Z","timestamp":1717433148000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbae254\/7686601"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,23]]},"references-count":30,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2024,5,23]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbae254","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2024,7]]},"published":{"date-parts":[[2024,5,23]]},"article-number":"bbae254"}}