Ontology highlight
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.
SUBMITTER: Wong JKL
PROVIDER: S-EPMC10469441 | biostudies-literature | 2023 Aug
REPOSITORIES: biostudies-literature
Wong John K L JKL Jassowicz Lena L Herold-Mende Christel C Seiffert Martina M Mallm Jan-Philipp JP Lichter Peter P Zapatka Marc M
BMC bioinformatics 20230831 1
<h4>Background</h4>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.<h4>Results</h4>The pipeline was tested on both single-cell and single-nuclei based RNA sequencin ...[more]