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 a team led by researchers at Loma Linda University presents 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. The researchers believe the datasets they 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.
Availability – All sequence data have been deposited in the National Center for Biotechnology Information (NCBI) Sequence Reads Archive (SRA) with accession ID: SRP199641 (BioProject: PRJNA504037)