ArticleGenome biology2020
GMM-Demux: sample demultiplexing, multiplet detection, experiment planning, and novel cell-type verification in single cell sequencing.
Article in Genome biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
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Who cites it
55 citing papers in PubMed.
- Moderated designs can balance between batch-effect mitigation and cell loss due to hashtag-assisted pooling in single-cell experiments.Genome research · 2026Article
- Lung Resident T Cells Across the Spectrum of TB Infection and Disease.bioRxiv : the preprint server for biology · 2026Article
- Antigenic stimulation in conjunction with cytokine is required for mediating IL-17A production in human MAIT cells.Scientific reports · 2026Article
- CellBouncer, a unified toolkit for single-cell demultiplexing and ambient RNA analysis, reveals hominid mitochondrial incompatibilities.Cell genomics · 2026Article
- Human neonatal MR1T cells have more diverse TCR repertoires but reduced bacterial recognition than adult MR1T cells.Nature communications · 2026Article
- CMDdemux: an efficient single cell demultiplexing method.Nucleic acids research · 2026Article
- Antigenic stimulation in conjunction with cytokine is required for mediating IL-17A production in human MAIT cells.bioRxiv : the preprint server for biology · 2026Article
- T cell antigenic recognition sequencing (TAR-seq) enables precise characterization of vaccine-elicited cellular immunity ex vivo andFrontiers in immunology · 2026Article
- Methodologies for Sample Multiplexing and Computational Deconvolution in Single-Cell Sequencing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Probability of stealth multiplets in sample-multiplexing for droplet-based single-cell analysis.BMC genomics · 2025Article
- Benchmarking of computational demultiplexing methods for single-nucleus RNA sequencing data.Briefings in bioinformatics · 2025Article
- Enhanced interpretation of immune cell phenotype and function through a rhesus macaque single-cell atlas.Cell genomics · 2025Article
- Human Neonatal MR1T Cells Have Diverse TCR Usage, are Less Cytotoxic and are Unable to Respond to Many Common Childhood Pathogens.bioRxiv : the preprint server for biology · 2025Article
- Characterization and bioinformatic filtering of ambient gRNAs in single-cell CRISPR screens using CLEANSER.Cell genomics · 2025Article
- Systematic benchmark of single-cell hashtag demultiplexing approaches reveals robust performance of a clustering-based method.Briefings in functional genomics · 2025Article
- An immune-focused supplemental alignment pipeline captures information missed from dominant single-cell RNA-seq analyses, including allele-specific MHC-I regulation.Frontiers in immunology · 2025Article
- Multiplets in scRNA-seq data: Extent of the problem and efficacy of methods for removal.PloS one · 2025Article
- Toti-N-glycan Recognition Enables Universal Multiplexed Single-Nucleus RNA Sequencing.Research (Washington, D.C.) · 2025Article
- Single-Cell Transcriptomics Reveals a Pivotal Role of DOCK2 in Sjögren Disease.ACR open rheumatology · 2024Article
- Spatially resolved single-cell atlas unveils a distinct cellular signature of fatal lung COVID-19 in a Malawian population.Nature medicine · 2024Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Identifying and removing multiplets are essential to improving the scalability and the reliability of single cell RNA sequencing (scRNA-seq). Multiplets create artificial cell types in the dataset. We propose a Gaussian mixture model-based multiplet identification method, GMM-Demux. GMM-Demux accurately identifies and removes multiplets through sample barcoding, including cell hashing and MULTI-seq. GMM-Demux uses a droplet formation model to authenticate putative cell types discovered from a scRNA-seq dataset. We generate two in-house cell-hashing datasets and compared GMM-Demux against three state-of-the-art sample barcoding classifiers. We show that GMM-Demux is stable and highly accurate and recognizes 9 multiplet-induced fake cell types in a PBMC dataset.
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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.