Comparative Analysis of Single-Cell RNA Sequencing Methods.
Mol Cell
; 65(4): 631-643.e4, 2017 Feb 16.
Article
em En
| MEDLINE
| ID: mdl-28212749
ABSTRACT
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.Palavras-chave
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
RNA
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Análise de Sequência de RNA
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Células-Tronco Embrionárias
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Análise de Célula Única
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Sequenciamento de Nucleotídeos em Larga Escala
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article
País de afiliação:
Alemanha