CellBouncer, A Unified Toolkit for Single-Cell Demultiplexing and Ambient RNA Analysis, Reveals Hominid Mitochondrial Incompatibilities

Pooled processing, in which cells from multiple sources are cultured or captured together, is an increasingly popular strategy for droplet-based single cell sequencing studies. This design allows efficient scaling of experiments, isolation of cell-intrinsic differences, and mitigation of batch effects. We present CellBouncer, a computational toolkit for demultiplexing and analyzing single-cell sequencing data from pooled experiments. We demonstrate that CellBouncer can separate and quantify multi-species and multi-individual cell mixtures, identify unknown mitochondrial haplotypes in cells, assign treatments from lipid-conjugated barcodes or CRISPR sgRNAs, and infer pool composition, outperforming existing methods. We also introduce methods to quantify ambient RNA contamination per cell, infer individual donors contributions to the ambient RNA pool, and determine a consensus doublet rate harmonized across data types. Applying these tools to tetraploid composite cells, we identify a competitive advantage of human over chimpanzee mitochondria across 10 cell fusion lines and provide evidence for inter-mitochondrial incompatibility and mito-nuclear incompatibility between species.