demuxSNP: supervised demultiplexing single-cell RNA sequencing using cell hashing and SNPs
(2024) GigaScience — Vol. 13, p. 1-12 (2024)
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- Bac kgr ound: Multiplexing single-cell RN A sequencing experiments reduces sequencing cost and facilitates lar ger-scale studies. Ho w-ever, factors such as cell hashing quality and class size imbalance impact demultiplexing algorithm performance, reducing cost-effecti v eness. Findings: We propose a supervised algorithm, demuxSNP, which leverages both cell hashing and genetic variation between individuals (single-n ucletotide pol ymorphisms [SNPs]). dem uxSNP addr esses fundamental limitations in dem ultiplexing methods that use onl y 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 negati v e, uncertain, or doub let using a near est-neighbor approach adapted for missing data. We benchmarked dem uxSNP a gainst hashing, genotype-fr ee SNP and hybrid methods on sim ulated and r eal data fr om r enal cell cancer. demuxSNP outperformed standalone hashing methods on low-quality hashing data benchmark, impr ov ed ov erall classification accuracy, and allowed more high RNA quality cells to be r ecov er ed. Thr ough v ar ying sim ulated doub let r ates, w e show ed that genotype-free SNP and hybrid methods that lev era ge them wer e impacted by class size imbalance and doublet r ate. demuxSNP's supervised approach was more robust to doublet rate in experiments with class size imbalance. Conclusions: 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 5-50% doublets are publicly available. demuxSNP is av aila b le as an R/Bioconductor packa ge (https://doi.org/doi:10.18129/B9.bioc.demuxSNP).
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Citations
Lynch, M., Wang, Y., Sui, S., Gatto, L., & Culhane, A. (2024). demuxSNP: supervised demultiplexing single-cell RNA sequencing using cell hashing and SNPs. GigaScience, 13, 1-12. https://doi.org/10.1093/gigascience/giae090 (Original work published 2024)