Souporcell : robust clustering of single-cell RNA-seq data by genotype without reference genotypes Heaton, H. /Talman, Arthur Knights, A. Imaz, M. Gaffney, D. J. Durbin, R. Hemberg, M. Lawniczak, M. K. N. 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. 2020 text https://www.documentation.ird.fr/hor/fdi:010079057 fdi:010079057 Heaton H., Talman Arthur, Knights A., Imaz M., Gaffney D. J., Durbin R., Hemberg M., Lawniczak M. K. N.. Souporcell : robust clustering of single-cell RNA-seq data by genotype without reference genotypes. 2020, 17 (6), 615-620 EN