ArticleNAR genomics and bioinformatics2023
Benchmarking single-cell hashtag oligo demultiplexing methods.
Article in NAR genomics and bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 29 citations in OpenAlex.
- Moderated designs can balance between batch-effect mitigation and cell loss due to hashtag-assisted pooling in single-cell experiments.Genome research · 2026Article
- CellBouncer, a unified toolkit for single-cell demultiplexing and ambient RNA analysis, reveals hominid mitochondrial incompatibilities.Cell genomics · 2026Article
- CMDdemux: an efficient single cell demultiplexing method.Nucleic acids research · 2026Article
- Methodologies for Sample Multiplexing and Computational Deconvolution in Single-Cell Sequencing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Accurate sample deconvolution of pooled snRNA-seq using sex-dependent gene expression patterns.NAR genomics and bioinformatics · 2025Article
- Moderated designs can balance between batch-effect mitigation and cell loss due to hashtag-assisted pooling in single-cell experiments.bioRxiv : the preprint server for biology · 2025Article
- Ensemblex: an accuracy-weighted ensemble genetic demultiplexing framework for population-scale scRNAseq sample pooling.Genome biology · 2025Article
- Accurate sample deconvolution of pooled snRNA-seq using sex-dependent gene expression patterns.bioRxiv : the preprint server for biology · 2025Article
- Systematic benchmark of single-cell hashtag demultiplexing approaches reveals robust performance of a clustering-based method.Briefings in functional genomics · 2025Article
- A hybrid demultiplexing strategy that improves performance and robustness of cell hashing.Briefings in bioinformatics · 2024Article
- hadge: a comprehensive pipeline for donor deconvolution in single-cell studies.Genome biology · 2024Article
- deMULTIplex2: robust sample demultiplexing for scRNA-seq.Genome biology · 2024Article
- demuxSNP: supervised demultiplexing single-cell RNA sequencing using cell hashing and SNPs.GigaScience · 2024Article
- Demultiplexing of single-cell RNA-sequencing data using interindividual variation in gene expression.Bioinformatics advances · 2024Article
- Performance of computational algorithms to deconvolve heterogeneous bulk ovarian tumor tissue depends on experimental factors.Genome biology · 2023Article
- demuxmix: demultiplexing oligonucleotide-barcoded single-cell RNA sequencing data with regression mixture models.Bioinformatics (Oxford, England) · 2023Article
- deMULTIplex2: robust sample demultiplexing for scRNA-seq.bioRxiv : the preprint server for biology · 2023Article
- scDemultiplex: An iterative beta-binomial model-based method for accurate demultiplexing with hashtag oligos.Computational and structural biotechnology journal · 2023Article
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sample multiplexing is often used to reduce cost and limit batch effects in single-cell RNA sequencing (scRNA-seq) experiments. A commonly used multiplexing technique involves tagging cells prior to pooling with a hashtag oligo (HTO) that can be sequenced along with the cells' RNA to determine their sample of origin. Several tools have been developed to demultiplex HTO sequencing data and assign cells to samples. In this study, we critically assess the performance of seven HTO demultiplexing tools: hashedDrops, HTODemux, GMM-Demux, demuxmix, deMULTIplex, BFF (bimodal flexible fitting) and HashSolo. The comparison uses data sets where each sample has also been demultiplexed using genetic variants from the RNA, enabling comparison of HTO demultiplexing techniques against complementary data from the genetic 'ground truth'. We find that all methods perform similarly where HTO labelling is of high quality, but methods that assume a bimodal count distribution perform poorly on lower quality data. We also suggest heuristic approaches for assessing the quality of HTO counts in an scRNA-seq experiment.
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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.