Comparative Analysis of Droplet-Based Ultra-High-Throughput Single-Cell RNA-Seq Systems

Mol Cell. 2019 Jan 3;73(1):130-142.e5. doi: 10.1016/j.molcel.2018.10.020. Epub 2018 Nov 21.


Since its establishment in 2009, single-cell RNA sequencing (RNA-seq) has been a major driver behind progress in biomedical research. In developmental biology and stem cell studies, the ability to profile single cells confers particular benefits. Although most studies still focus on individual tissues or organs, the recent development of ultra-high-throughput single-cell RNA-seq has demonstrated potential power in characterizing more complex systems or even the entire body. However, although multiple ultra-high-throughput single-cell RNA-seq systems have attracted attention, no systematic comparison of these systems has been performed. Here, with the same cell line and bioinformatics pipeline, we developed directly comparable datasets for each of three widely used droplet-based ultra-high-throughput single-cell RNA-seq systems, inDrop, Drop-seq, and 10X Genomics Chromium. Although each system is capable of profiling single-cell transcriptomes, their detailed comparison revealed the distinguishing features and suitable applications for each system.

Keywords: 10X genomics; Drop-seq; RNA-Seq analysis pipeline; barcode analysis; droplet-based microfluidics; high throughput; inDrop; method comparison; single-cell RNA-seq.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Automation, Laboratory
  • Base Sequence
  • Cell Line
  • Computational Biology
  • Cost-Benefit Analysis
  • DNA Barcoding, Taxonomic
  • Gene Expression Profiling / economics
  • Gene Expression Profiling / methods*
  • High-Throughput Nucleotide Sequencing* / economics
  • Humans
  • Microfluidic Analytical Techniques* / economics
  • RNA / genetics*
  • Reproducibility of Results
  • Sequence Analysis, RNA / economics
  • Sequence Analysis, RNA / methods*
  • Single-Cell Analysis / economics
  • Single-Cell Analysis / methods*
  • Transcriptome*
  • Workflow


  • RNA