Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, Großhaderner Straße 2, 82152 Martinsried, Germany.
Ludwig Institute for Cancer Research, Box 240, 171 77 Stockholm, Sweden; Department of Cell and Molecular Biology, Karolinska Institutet, 171 77 Stockholm, Sweden.
Mol Cell. 2017 Feb 16;65(4):631-643.e4. doi: 10.1016/j.molcel.2017.01.023.
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.
单细胞 RNA 测序 (scRNA-seq) 为解决生物学和医学问题提供了新的可能性。然而，不同 scRNA-seq 方案的性能缺乏系统比较。我们从 583 个小鼠胚胎干细胞中生成数据，以评估六种主要的 scRNA-seq 方法：CEL-seq2、Drop-seq、MARS-seq、SCRB-seq、Smart-seq 和 Smart-seq2。虽然 Smart-seq2 每个细胞和跨细胞检测到的基因最多，但由于使用了独特分子标识符 (UMIs)，CEL-seq2、Drop-seq、MARS-seq 和 SCRB-seq 量化 mRNA 水平的扩增噪声更小。在不同测序深度下的功率模拟表明，Drop-seq 对于大量细胞的转录组定量更具成本效益，而 MARS-seq、SCRB-seq 和 Smart-seq2 在分析较少细胞时效率更高。我们的定量比较为在六种主要的 scRNA-seq 方法之间做出明智的选择提供了基础，并为进一步改进 scRNA-seq 方案提供了基准测试框架。
