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A Multi-center Cross-platform Single-cell RNA Sequencing Reference Dataset

By Xin Chen, Zhaowei Yang, Wanqiu Chen, Yongmei Zhao, Andrew Farmer, Bao Tran, Vyacheslav Furtak, Malcolm Moos, Wenming Xiao, Charles Wang

Posted 21 Sep 2020
bioRxiv DOI: 10.1101/2020.09.20.305474 (published DOI: 10.1038/s41597-021-00809-x)

Single-cell RNA sequencing (scRNA-seq) is developing rapidly, and investigators seeking to use this technology are left with a variety of options for both experimental platform and bioinformatics methods. There is an urgent need for scRNA-seq reference datasets for benchmarking of different scRNA-seq platforms and bioinformatics methods. To be broadly applicable, these should be generated from renewable, well characterized reference samples and processed in multiple centers across different platforms. Here we present a benchmarking scRNA-seq dataset that includes 20 scRNA-seq datasets acquired either as a mixtures or as individual samples from two biologically distinct cell lines for which a large amount of multi-platform whole genome sequencing data are also available. These scRNA-seq datasets were generated from multiple popular platforms across four sequencing centers. Our benchmark datasets provide a resource that we believe will have great value for the single-cell community by serving as a reference dataset for evaluating various bioinformatics methods for scRNA-seq analyses, including but not limited to data preprocessing, imputation, normalization, clustering, batch correction, and differential analysis. ### Competing Interest Statement The authors have declared no competing interest.

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