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Open Access Green as soon as Postprint is submitted to ZB.
Single cells make big data: New challenges and opportunities in transcriptomics.
Curr. Opin. Syst. Biol. 4, 85-91 (2017)
Recent technological advances have enabled unprecedented insight into transcriptomics at the level of single cells. Single cell transcriptomics enables the measurement of tran- scriptomic information of thousands of single cells in a single experiment. The volume and complexity of resulting data make it a paradigm of big data. Consequently, the field is presented with new scientific and, in particular, analytical challenges where currently no scalable solutions exist. At the same time, exciting opportunities arise from increased resolution of single- cell RNA sequencing data and improved statistical power of ever growing datasets. Big single cell RNA sequencing data promises valuable insights into cellular heterogeneity which may significantly improve our understanding of biology and human disease. This review focuses on single cell tran- scriptomics and highlights the inherent opportunities and challenges in the context of big data analytics.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Single-cell RNA-seq, Big data, Single-cell transcriptomics, Machine
learning
ISSN (print) / ISBN
2452-3100
e-ISSN
2452-3100
Quellenangaben
Volume: 4,
Pages: 85-91
Publisher
Elsevier
Publishing Place
Amsterdam
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Computational Biology (ICB)