Comparative analysis of single-cell RNA sequencing methods
Transcriptomics Dataset
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General Information
| Accession | GSE75790 |
| Title | Comparative analysis of single-cell RNA sequencing methods |
| Description | 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 provides a framework for benchmarking further improvements of scRNA-seq protocols. |
| Landing Page | https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE75790 |
| Repository | Gene Expression Omnibus |
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