What question did this study set out to answer?

To examine how single-cell genomic and proteomic technologies resolve cellular heterogeneity, uncover novel cell types, and map dynamic transitions across developmental landscapes.

October 1, 2015Genome ResearchOpen Access

Defining cell types and states with single-cell genomics

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To examine how single-cell genomic and proteomic technologies resolve cellular heterogeneity, uncover novel cell types, and map dynamic transitions across developmental landscapes.
Reviewed single-cell genomic and proteomic methodologies capable of measuring global gene regulation across thousands of individual cells in single experiments.
Evaluated computational and theoretical frameworks, including Waddington's epigenetic landscape, to interpret cell states and trajectory transitions relative to traditional bulk population assays.
Single-cell profiling overcomes the averaging artifacts of bulk population measurements, enabling the identification of rare cell types and distinct transitional states.
High-resolution measurements map continuous developmental trajectories and identify the molecular regulators that govern cell state transitions in health and disease.
Ongoing development of experimental throughput and computational modeling is required to fully resolve the molecular landscapes defining cellular identity.

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Implication

Review reveals high-resolution mapping of cellular states and transitions via single-cell genomics, highlighting molecular mechanisms underlying development and disease.

Cite This Study

Cole Trapnell (2015) studied this question.

synapsesocial.com/papers/69daa5c0387cf7069868738d https://doi.org/10.1101/gr.190595.115

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Implication

Review reveals high-resolution mapping of cellular states and transitions via single-cell genomics, highlighting molecular mechanisms underlying development and disease.

Defining cell types and states with single-cell genomics

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Discussion

Implication

Cite This Study

Defining cell types and states with single-cell genomics

Key Points

Discussion

Implication

Cite This Study

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