{"doi":"10.1038/nbt.4042","title":"Multiplexed droplet single-cell RNA-sequencing using natural genetic variation","abstract":"Droplet single-cell RNA-sequencing (dscRNA-seq) has enabled rapid, massively parallel profiling of transcriptomes. However, assessing differential expression across multiple individuals has been hampered by inefficient sample processing and technical batch effects. Here we describe a computational tool, demuxlet, that harnesses natural genetic variation to determine the sample identity of each droplet containing a single cell (singlet) and detect droplets containing two cells (doublets). These capabilities enable multiplexed dscRNA-seq experiments in which cells from unrelated individuals are pooled and captured at higher throughput than in standard workflows. Using simulated data, we show that 50 single-nucleotide polymorphisms (SNPs) per cell are sufficient to assign 97% of singlets and identify 92% of doublets in pools of up to 64 individuals. Given genotyping data for each of eight pooled samples, demuxlet correctly recovers the sample identity of >99% of singlets and identifies doublets at rates consistent with previous estimates. We apply demuxlet to assess cell-type-specific changes in gene expression in 8 pooled lupus patient samples treated with interferon (IFN)-β and perform eQTL analysis on 23 pooled samples.","journal":"Nature Biotechnology","year":2017,"id":10237,"datarank":1.0714241101742432,"base_score":7.142827401161621,"endowment":7.142827401161621,"self_citation_contribution":1.0714241101742432,"citation_network_contribution":0.0,"self_endowment_contribution":1.0714241101742432,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1264,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.0569,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2017-12-11","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":15882,"name":"Meena Subramaniam","orcid":"0000-0003-1534-567X","position":1,"is_corresponding":false},{"id":24088,"name":"Sasha Targ","orcid":"0009-0006-1510-2589","position":2,"is_corresponding":false},{"id":86159,"name":"Michelle Nguyen","orcid":"0000-0001-7792-754X","position":3,"is_corresponding":false},{"id":24096,"name":"Lenka Maliskova","orcid":"0000-0001-7677-3833","position":4,"is_corresponding":false},{"id":1348,"name":"Elizabeth McCarthy","orcid":"0000-0002-0073-4069","position":5,"is_corresponding":false},{"id":86160,"name":"Eunice Wan","orcid":null,"position":6,"is_corresponding":false},{"id":86161,"name":"Simon Wong","orcid":"0000-0002-5503-4510","position":7,"is_corresponding":false},{"id":86162,"name":"Lauren E. Byrnes","orcid":"0000-0001-5991-8201","position":8,"is_corresponding":false},{"id":24094,"name":"Cristina M. Lanata","orcid":"0000-0002-6017-4921","position":9,"is_corresponding":false},{"id":15881,"name":"Rachel E. Gate","orcid":null,"position":10,"is_corresponding":false},{"id":5261,"name":"Sara Mostafavi","orcid":"0000-0003-4698-1177","position":11,"is_corresponding":false},{"id":30775,"name":"Alexander Marson","orcid":"0000-0002-2734-5776","position":12,"is_corresponding":false},{"id":24103,"name":"Noah Zaitlen","orcid":"0000-0002-3553-3670","position":13,"is_corresponding":false},{"id":2822,"name":"Lindsey A. Criswell","orcid":"0000-0002-0761-7543","position":14,"is_corresponding":false},{"id":2802,"name":"Chun Jimmie Ye","orcid":"0000-0001-6560-3783","position":15,"is_corresponding":false},{"id":24782,"name":"Hyun Min Kang","orcid":"0000-0002-3631-3979","position":0,"is_corresponding":true}],"reference_count":40,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-03-01T18:20:47.508186Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}