Abstract

Single-cell genomics has now made it possible to create a comprehensive atlas of human cells. At the same time, it has reopened definitions of a cell's identity and of the ways in which identity is regulated by the cell's molecular circuitry. Emerging computational analysis methods, especially in single-cell RNA sequencing (scRNA-seq), have already begun to reveal, in a data-driven way, the diverse simultaneous facets of a cell's identity, from discrete cell types to continuous dynamic transitions and spatial locations. These developments will eventually allow a cell to be represented as a superposition of 'basis vectors', each determining a different (but possibly dependent) aspect of cellular organization and function. However, computational methods must also overcome considerable challenges-from handling technical noise and data scale to forming new abstractions of biology. As the scale of single-cell experiments continues to increase, new computational approaches will be essential for constructing and characterizing a reference map of cell identities.

Keywords

Computer scienceComputational biologyIdentity (music)GenomicsCell functionComputational modelFunction (biology)CellBiologyArtificial intelligenceGenomeCell biologyGenetics

MeSH Terms

AnimalsCell Physiological PhenomenaComputer SimulationGene Expression ProfilingGene Expression RegulationHigh-Throughput Nucleotide SequencingHumansModelsBiologicalProteomeSignal TransductionTranscriptome

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Publication Info

Year
2016
Type
review
Volume
34
Issue
11
Pages
1145-1160
Citations
668
Access
Closed

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Social media, news, blog, policy document mentions

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668
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7
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Cite This

Allon Wagner, Aviv Regev, Nir Yosef (2016). Revealing the vectors of cellular identity with single-cell genomics. Nature Biotechnology , 34 (11) , 1145-1160. https://doi.org/10.1038/nbt.3711

Identifiers

DOI
10.1038/nbt.3711
PMID
27824854
PMCID
PMC5465644

Data Quality

Data completeness: 86%