Molecular Cell
Volume 65, Issue 4, 16 February 2017, Pages 631-643.e4
Journal home page for Molecular Cell

Article
Comparative Analysis of Single-Cell RNA Sequencing Methods

https://doi.org/10.1016/j.molcel.2017.01.023Get rights and content
Under an Elsevier user license
open archive

Highlights

  • The study represents the most comprehensive comparison of scRNA-seq protocols

  • Power simulations quantify the effect of sensitivity and precision on cost efficiency

  • The study offers an informed choice among six prominent scRNA-seq methods

  • The study provides a framework for benchmarking future protocol improvements

Summary

Single-cell RNA sequencing (scRNA-seq) offers new possibilities to address biological and medical questions. However, systematic comparisons of the performance of diverse scRNA-seq protocols are lacking. We generated data from 583 mouse embryonic stem cells to evaluate six prominent scRNA-seq methods: CEL-seq2, Drop-seq, MARS-seq, SCRB-seq, Smart-seq, and Smart-seq2. While Smart-seq2 detected the most genes per cell and across cells, CEL-seq2, Drop-seq, MARS-seq, and SCRB-seq quantified mRNA levels with less amplification noise due to the use of unique molecular identifiers (UMIs). Power simulations at different sequencing depths showed that Drop-seq is more cost-efficient for transcriptome quantification of large numbers of cells, while MARS-seq, SCRB-seq, and Smart-seq2 are more efficient when analyzing fewer cells. Our quantitative comparison offers the basis for an informed choice among six prominent scRNA-seq methods, and it provides a framework for benchmarking further improvements of scRNA-seq protocols.

Keywords

single-cell RNA-seq
method comparison
transcriptomics
power analysis
simulation
cost-effectiveness

Cited by (0)

7

Lead Contact