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Respirology
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Respirology
Article . 2018 . Peer-reviewed
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Respirology
Article . 2020
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Transcriptomics and single‐cell RNA‐sequencing

Authors: Daniel C. Chambers; Alan M. Carew; Samuel W. Lukowski; Joseph E. Powell;

Transcriptomics and single‐cell RNA‐sequencing

Abstract

ABSTRACTThe past four decades have yielded advances in molecular biology allowing detailed characterization of the cellular genome and the transcriptome: the complete set of RNA species transcribed by a cell or tissue. Through transcriptomics and next‐generation sequencing, we can now attain an unprecedented level of detail in understanding cellular phenotypes through examining the genes expressed in specific physiological and pathological states. In this review, we provide an overview of transcriptomics and RNA‐sequencing in the analysis of whole tissue and single cells. We describe the techniques and pitfalls involved in the isolation and sequencing of single cells, and what additional benefits this application can provide. Finally, we look to how these technologies are being applied in pulmonary research, and how they may translate in the near future into clinical practice.

Country
Australia
Keywords

Lung Diseases, Biomedical Research, Biomedical Technology, Translational Research, Biomedical, ribonucleic acid sequencing, 2740 Pulmonary and Respiratory Medicine, single-cell analysis, Humans, Transcriptome, transcriptome, Sequence Analysis, pulmonary disease

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    96
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
96
Top 1%
Top 10%
Top 10%
bronze