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Quantitative single-cell transcriptomics.


ABSTRACT: Single-cell RNA sequencing (scRNA-seq) is currently transforming our understanding of biology, as it is a powerful tool to resolve cellular heterogeneity and molecular networks. Over 50 protocols have been developed in recent years and also data processing and analyzes tools are evolving fast. Here, we review the basic principles underlying the different experimental protocols and how to benchmark them. We also review and compare the essential methods to process scRNA-seq data from mapping, filtering, normalization and batch corrections to basic differential expression analysis. We hope that this helps to choose appropriate experimental and computational methods for the research question at hand.

SUBMITTER: Ziegenhain C 

PROVIDER: S-EPMC6063296 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Quantitative single-cell transcriptomics.

Ziegenhain Christoph C   Vieth Beate B   Parekh Swati S   Hellmann Ines I   Enard Wolfgang W  

Briefings in functional genomics 20180701 4


Single-cell RNA sequencing (scRNA-seq) is currently transforming our understanding of biology, as it is a powerful tool to resolve cellular heterogeneity and molecular networks. Over 50 protocols have been developed in recent years and also data processing and analyzes tools are evolving fast. Here, we review the basic principles underlying the different experimental protocols and how to benchmark them. We also review and compare the essential methods to process scRNA-seq data from mapping, filt  ...[more]

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