{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T14:29:07Z","timestamp":1771079347153,"version":"3.50.1"},"reference-count":47,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2024,11,28]],"date-time":"2024-11-28T00:00:00Z","timestamp":1732752000000},"content-version":"vor","delay-in-days":332,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Chan Zuckerberg Initiative DAF","award":["CZF 2019-002,443"],"award-info":[{"award-number":["CZF 2019-002,443"]}]},{"DOI":"10.13039\/100000923","name":"Silicon Valley Community Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000923","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007269","name":"School of Medicine","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007269","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001635","name":"University of Limerick","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001635","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000005","name":"U.S. Department of Defense","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000005","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Kidney Cancer Research Program"},{"name":"FY21 Translational Research Partnership Award","award":["W81XWH-21-1-0442"],"award-info":[{"award-number":["W81XWH-21-1-0442"]}]},{"name":"FY21 Idea Development Award","award":["W81XWH-21-1-0482"],"award-info":[{"award-number":["W81XWH-21-1-0482"]}]},{"name":"Wong Family Award"},{"name":"Kidney Cancer Association Trailblazer Award"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,1,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Multiplexing single-cell RNA sequencing experiments reduces sequencing cost and facilitates larger-scale studies. However, factors such as cell hashing quality and class size imbalance impact demultiplexing algorithm performance, reducing cost-effectiveness.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Findings<\/jats:title>\n                  <jats:p>We propose a supervised algorithm, demuxSNP, which leverages both cell hashing and genetic variation between individuals (single-nucletotide polymorphisms [SNPs]). demuxSNP addresses fundamental limitations in demultiplexing methods that use only one data modality. Some cells may be confidently demultiplexed using probabilistic hashing methods. demuxSNP uses these data to infer the genotype of singlet and doublet clusters and predict on cells assigned as negative, uncertain, or doublet using a nearest-neighbor approach adapted for missing data.<\/jats:p>\n                  <jats:p>We benchmarked demuxSNP against hashing, genotype-free SNP and hybrid methods on simulated and real data from renal cell cancer. demuxSNP outperformed standalone hashing methods on low-quality hashing data benchmark, improved overall classification accuracy, and allowed more high RNA quality cells to be recovered. Through varying simulated doublet rates, we showed that genotype-free SNP and hybrid methods that leverage them were impacted by class size imbalance and doublet rate. demuxSNP\u2019s supervised approach was more robust to doublet rate in experiments with class size imbalance.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>demuxSNP uses hashing and SNP data to demultiplex datasets with low hashing quality where biological samples are genetically distinct. Unassigned or negative cells with high RNA quality are recovered, making more cells available for analysis. Data simulation and benchmarking pipelines as well as processed benchmarking data for 5\u201350% doublets are publicly available. demuxSNP is available as an R\/Bioconductor package (https:\/\/doi.org\/doi:10.18129\/B9.bioc.demuxSNP).<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/gigascience\/giae090","type":"journal-article","created":{"date-parts":[[2024,11,28]],"date-time":"2024-11-28T16:37:32Z","timestamp":1732811852000},"source":"Crossref","is-referenced-by-count":2,"title":["demuxSNP: supervised demultiplexing single-cell RNA sequencing using cell hashing and SNPs"],"prefix":"10.1093","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9535-6461","authenticated-orcid":false,"given":"Michael P","family":"Lynch","sequence":"first","affiliation":[{"name":"School of Medicine, Limerick Digital Cancer Research Centre, Health Research Institute (HRI), University of Limerick , Limerick V94 T9PX ,","place":["Ireland"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2573-0611","authenticated-orcid":false,"given":"Yufei","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute , Boston, MA 02215 ,","place":["USA"]},{"name":"Harvard Medical School , Boston, MA 02115 ,","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6191-4709","authenticated-orcid":false,"given":"Shannan","family":"Ho\u00a0Sui","sequence":"additional","affiliation":[{"name":"Harvard T.H. Chan School of Public Health , Boston, MA 02215 ,","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1520-2268","authenticated-orcid":false,"given":"Laurent","family":"Gatto","sequence":"additional","affiliation":[{"name":"Computational Biology and Bioinformatics Unit (CBIO), de Duve Institute , Universit\u00e9 catholique de Louvain, Brussels 1200 ,","place":["Belgium"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1395-9734","authenticated-orcid":false,"given":"Aedin C","family":"Culhane","sequence":"additional","affiliation":[{"name":"School of Medicine, Limerick Digital Cancer Research Centre, Health Research Institute (HRI), University of Limerick , Limerick V94 T9PX ,","place":["Ireland"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2024,11,28]]},"reference":[{"key":"2024112816371175600_bib1","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1007\/978-1-0716-0849-4_9","article-title":"Statistical and bioinformatics analysis of data from bulk and single-cell RNA sequencing experiments","volume":"2194","author":"Yu","year":"2021","journal-title":"Methods Mol Biol"},{"key":"2024112816371175600_bib2","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1038\/s41368-021-00146-0","article-title":"From bulk, single-cell to spatial RNA sequencing","volume":"13","author":"Li","year":"2021","journal-title":"Int J Oral Sci"},{"key":"2024112816371175600_bib3","doi-asserted-by":"publisher","first-page":"96","DOI":"10.3390\/diseases11030096","article-title":"The contribution of multiplexing single cell RNA sequencing in acute myeloid leukemia","volume":"11","author":"Madaci","year":"2023","journal-title":"Diseases"},{"key":"2024112816371175600_bib4","doi-asserted-by":"publisher","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":"2024112816371175600_bib5","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1038\/s41592-019-0433-8","article-title":"MULTI-seq: universal sample multiplexing for single-cell RNA sequencing using lipid-tagged indices","volume":"16","author":"McGinnis","year":"2019","journal-title":"Nat Methods"},{"key":"2024112816371175600_bib27","doi-asserted-by":"publisher","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 Genomics Bioinformatics"},{"key":"2024112816371175600_bib7","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1186\/s13059-022-02628-8","article-title":"Comparative analysis of antibody- and lipid-based multiplexing methods for single-cell RNA-seq","volume":"23","author":"Mylka","year":"2022","journal-title":"Genome Biol"},{"key":"2024112816371175600_bib8","doi-asserted-by":"publisher","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":"2024112816371175600_bib9","doi-asserted-by":"publisher","first-page":"326","DOI":"10.1186\/s12859-023-05440-8","article-title":"scSNPdemux: a sensitive demultiplexing pipeline using single nucleotide polymorphisms for improved pooled single-cell RNA sequencing analysis","volume":"24","author":"Wong","year":"2023","journal-title":"BMC Bioinf"},{"key":"2024112816371175600_bib10","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1186\/s13059-019-1865-2","article-title":"Bayesian demultiplexing of pooled single-cell RNA-seq data without genotype reference","volume":"20","author":"Huang","year":"2019","journal-title":"Genome Biol"},{"key":"2024112816371175600_bib11","doi-asserted-by":"publisher","first-page":"290","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":"2024112816371175600_bib12","doi-asserted-by":"publisher","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":"2024112816371175600_bib13","doi-asserted-by":"publisher","first-page":"803","DOI":"10.1038\/s41587-023-01873-x","article-title":"Single-nucleotide variant calling in single-cell sequencing data with Monopogen","volume":"42","author":"Dou","year":"2024","journal-title":"Nat Biotechnol"},{"key":"2024112816371175600_bib14","doi-asserted-by":"crossref","unstructured":"Weber LM, Hippen AA, Hickey PF, et al. 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