Journal
NATURE METHODS
Volume 17, Issue 6, Pages 615-+Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41592-020-0820-1
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Funding
- Wellcome Trust [206194/Z/17/Z, WT098503]
- MRC Career Development Award [G1100339]
- NIHR/Wellcome Trust Clinical Research Facility
- UK Medical Research Council [MR/L003120/1]
- British Heart Foundation [RG/13/13/30194, RG/18/13/33946]
- National Institute for Health Research (Cambridge Biomedical Research Centre at the Cambridge University Hospital's NHS Foundation Trust)
- MRC [G1100339, MR/L003120/1] Funding Source: UKRI
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Souporcell clusters single-cell RNA-seq data using genotype information without the use of a genotype reference. Methods to deconvolve single-cell RNA-sequencing (scRNA-seq) data are necessary for samples containing a mixture of genotypes, whether they are natural or experimentally combined. Multiplexing across donors is a popular experimental design that can avoid batch effects, reduce costs and improve doublet detection. By using variants detected in scRNA-seq reads, it is possible to assign cells to their donor of origin and identify cross-genotype doublets that may have highly similar transcriptional profiles, precluding detection by transcriptional profile. More subtle cross-genotype variant contamination can be used to estimate the amount of ambient RNA. Ambient RNA is caused by cell lysis before droplet partitioning and is an important confounder of scRNA-seq analysis. Here we develop souporcell, a method to cluster cells using the genetic variants detected within the scRNA-seq reads. We show that it achieves high accuracy on genotype clustering, doublet detection and ambient RNA estimation, as demonstrated across a range of challenging scenarios.
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