A multi-center cross-platform single-cell RNA sequencing reference dataset

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 benchmark scRNA-seq dataset that includes 20 scRNA-seq datasets acquired either as 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. We believe the datasets we describe here will provide a resource that meets this need by allowing evaluation of various bioinformatics methods for scRNA-seq analyses, including but not limited to data preprocessing, imputation, normalization, clustering, batch correction, and differential analysis.

Automated summary

Single-cell RNA sequencing (scRNA-seq) is rapidly developing, offering investigators a variety of options for experimental platform and bioinformatics methods. There is an urgent need for scRNA-seq reference datasets for benchmarking, generated from renewable, well-characterized reference samples processed across different platforms in diverse centers. This benchmark scRNA-seq dataset includes 20 datasets from two biologically distinct cell lines, providing a resource for evaluating various bioinformatics methods for scRNA-seq analyses.