Validation samples for demultiplexing scRNAseq data by genotype in mixed genotype single cell RNAseq experiments without reference genotypes.. souporcell_validation

Methods to deconvolve single-cell RNA sequencing data are necessary for samples containing a mixture of genotypes whether natural or experimentally combined. Multiplexing across donors is a popular experimental design which can avoid batch effects, reduce costs, and improve doublet detection. Using variants detected in the RNAseq reads, it is possible to assign cells to their donor of origin and to 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 prior to droplet partitioning and is an important confounder of scRNAseq analysis. Souporcell is a novel method to cluster cells using the genetic variants detected within the scRNAseq 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.