Benchmarking Single-Cell RNA Sequencing Protocols for Cell Atlas Projects
By
Elisabetta Mereu,
Atefeh Lafzi,
Catia Moutinho,
Christoph Ziegenhain,
Davis J. MacCarthy,
Adrian Alvarez,
Eduard Batlle,
Sagar,
Dominic Grün,
Julia K. Lau,
Stéphane C Boutet,
Chad Sanada,
Aik Ooi,
Robert C. Jones,
Kelly Kaihara,
Chris Brampton,
Yasha Talaga,
Yohei Sasagawa,
Kaori Tanaka,
Tetsutaro Hayashi,
Itoshi Nikaido,
Cornelius Fischer,
Sascha Sauer,
Timo Trefzer,
Christian Conrad,
Xian Adiconis,
Lan T. Nguyen,
Aviv Regev,
Joshua Z. Levin,
Swati Parekh,
Aleksandar Janjic,
Lucas E. Wange,
Johannes W. Bagnoli,
Wolfgang Enard,
Ivo Glynne Gut,
Rickard Sandberg,
Ivo Gut,
Oliver Stegle,
Holger Heyn
Posted 13 May 2019
bioRxiv DOI: 10.1101/630087
(published DOI: 10.1038/s41587-020-0469-4)
Single-cell RNA sequencing (scRNA-seq) is the leading technique for charting the molecular properties of individual cells. The latest methods are scalable to thousands of cells, enabling in-depth characterization of sample composition without prior knowledge. However, there are important differences between scRNA-seq techniques, and it remains unclear which are the most suitable protocols for drawing cell atlases of tissues, organs and organisms. We have generated benchmark datasets to systematically evaluate techniques in terms of their power to comprehensively describe cell types and states. We performed a multi-center study comparing 13 commonly used single-cell and single-nucleus RNA-seq protocols using a highly heterogeneous reference sample resource. Comparative and integrative analysis at cell type and state level revealed marked differences in protocol performance, highlighting a series of key features for cell atlas projects. These should be considered when defining guidelines and standards for international consortia, such as the Human Cell Atlas project.
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