PT  - JOURNAL ARTICLE
AU  - Viacheslav Mylka
AU  - Jeroen Aerts
AU  - Irina Matetovici
AU  - Suresh Poovathingal
AU  - Niels Vandamme
AU  - Ruth Seurinck
AU  - Gert Hulselmans
AU  - Silvie Van Den Hoecke
AU  - Hans Wils
AU  - Joke Reumers
AU  - Jeroen Van Houdt
AU  - Stein Aerts
AU  - Yvan Saeys
TI  - Comparative analysis of antibody- and lipid-based multiplexing methods for single-cell RNA-seq
AID  - 10.1101/2020.11.16.384222
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.11.16.384222
4099  - http://biorxiv.org/content/early/2020/11/17/2020.11.16.384222.short
4100  - http://biorxiv.org/content/early/2020/11/17/2020.11.16.384222.full
AB  - Multiplexing of samples in single-cell RNA-seq studies allows significant reduction of experimental costs, straightforward identification of doublets, increased cell throughput, and reduction of sample-specific batch effects. Recently published multiplexing techniques using oligo-conjugated antibodies or - lipids allow barcoding sample-specific cells, a process called ‘hashing’. Here, we compare the hashing performance of TotalSeq-A and -C antibodies, custom synthesized lipids and MULTI-seq lipid hashes in four cell lines, both for single-cell RNA-seq and single-nucleus RNA-seq. Hashing efficiency was evaluated using the intrinsic genetic variation of the cell lines. Benchmarking of different hashing strategies and computational pipelines indicates that correct demultiplexing can be achieved with both lipid- and antibody-hashed human cells and nuclei, with MULTISeqDemux as the preferred demultiplexing function and antibody-based hashing as the most efficient protocol on cells. Antibody hashing was further evaluated on clinical samples using PBMCs from healthy and SARS-CoV-2 infected patients, where we demonstrate a more affordable approach for large single-cell sequencing clinical studies, while simultaneously reducing batch effects.Competing Interest StatementThe authors have declared no competing interest.