scSNPdemux: a sensitive demultiplexing pipeline using single nucleotide polymorphisms for improved pooled single-cell RNA sequencing analysis

Abstract

Background: Here we present scSNPdemux, a sample demultiplexing pipeline for single-cell RNA sequencing data using natural genetic variations in humans. The pipeline requires alignment files from Cell Ranger (10× Genomics), a population SNP database and genotyped single nucleotide polymorphisms (SNPs) per sample. The tool works on sparse genotyping data in VCF format for sample identification. Results: The pipeline was tested on both single-cell and single-nuclei based RNA sequencing datasets and showed superior demultiplexing performance over the lipid-based CellPlex and Multi-seq sample multiplexing technique which incurs additional single cell library preparation steps. Specifically, our pipeline demonstrated superior sensitivity and specificity in cell-identity assignment over CellPlex, especially on immune cell types with low RNA content. Conclusions: We designed a streamlined pipeline for single-cell sample demultiplexing, aiming to overcome common problems in multiplexing samples using single cell libraries which might affect data quality and can be costly.