Systematic comparison of single-cell and single-nucleus RNA-sequencing methods

Jiarui Ding, Xian Adiconis, Sean K. Simmons, Monika S. Kowalczyk, Cynthia C. Hession, Nemanja D. Marjanovic, Travis K. Hughes, Marc H. Wadsworth, Tyler Burks, Lan T. Nguyen, John Y.H. Kwon, Boaz Barak, William Ge, Amanda J. Kedaigle, Shaina Carroll, Shuqiang Li, Nir Hacohen, Orit Rozenblatt-Rosen, Alex K. Shalek, Alexandra Chloé VillaniAviv Regev, Joshua Z. Levin*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

431 Scopus citations

Abstract

The scale and capabilities of single-cell RNA-sequencing methods have expanded rapidly in recent years, enabling major discoveries and large-scale cell mapping efforts. However, these methods have not been systematically and comprehensively benchmarked. Here, we directly compare seven methods for single-cell and/or single-nucleus profiling—selecting representative methods based on their usage and our expertise and resources to prepare libraries—including two low-throughput and five high-throughput methods. We tested the methods on three types of samples: cell lines, peripheral blood mononuclear cells and brain tissue, generating 36 libraries in six separate experiments in a single center. To directly compare the methods and avoid processing differences introduced by the existing pipelines, we developed scumi, a flexible computational pipeline that can be used with any single-cell RNA-sequencing method. We evaluated the methods for both basic performance, such as the structure and alignment of reads, sensitivity and extent of multiplets, and for their ability to recover known biological information in the samples.

Original languageEnglish
Pages (from-to)737-746
Number of pages10
JournalNature Biotechnology
Volume38
Issue number6
DOIs
StatePublished - 1 Jun 2020
Externally publishedYes

Funding

FundersFunder number
Manton Foundation
National Institute of Mental HealthU19MH114821
National Human Genome Research InstituteRM1HG006193
National Cancer InstituteU2CCA233195
Office of Extramural Research, National Institutes of Health
Klarman Cell Observatory, Broad Institute

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