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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7854649PMC
http://dx.doi.org/10.1038/s41597-021-00809-xDOI Listing

Publication Analysis

Top Keywords

bioinformatics methods
12
single-cell rna
8
rna sequencing
8
scrna-seq datasets
8
scrna-seq
7
multi-center cross-platform
4
cross-platform single-cell
4
sequencing
4
sequencing reference
4
reference dataset
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!