%0 Journal Article
%9 ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES
%A Heaton, H.
%A Talman, Arthur
%A Knights, A.
%A Imaz, M.
%A Gaffney, D. J.
%A Durbin, R.
%A Hemberg, M.
%A Lawniczak, M. K. N.
%T Souporcell : robust clustering of single-cell RNA-seq data by genotype without reference genotypes
%D 2020
%L fdi:010079057
%G ENG
%J Nature Methods
%@ 1548-7091
%M ISI:000538122800024
%N 6
%P 615-620
%R 10.1038/s41592-020-0820-1
%U https://www.documentation.ird.fr/hor/fdi:010079057
%> https://www.documentation.ird.fr/intranet/publi/2020/05/010079057.pdf
%V 17
%W Horizon (IRD)
%X 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.
%$ 020