Abstract
<ns4:p>Single-cell RNA-sequencing methods are now robust and economically practical and are becoming a powerful tool for high-throughput, high-resolution transcriptomic analysis of cell states and dynamics. Single-cell approaches circumvent the averaging artifacts associated with traditional bulk population data, yielding new insights into the cellular diversity underlying superficially homogeneous populations. Thus far, single-cell RNA-sequencing has already shown great effectiveness in unraveling complex cell populations, reconstructing developmental trajectories, and modeling transcriptional dynamics. Ongoing technical improvements to single-cell RNA-sequencing throughput and sensitivity, the development of more sophisticated analytical frameworks for single-cell data, and an increasing array of complementary single-cell assays all promise to expand the usefulness and potential applications of single-cell transcriptomic profiling.</ns4:p>
Keywords
TranscriptomeComputational biologySingle cell sequencingSingle-cell analysisBiologyRNACellDNA sequencingRNA-SeqPopulationProfiling (computer programming)Computer scienceGeneticsGeneGene expressionPhenotypeExome sequencingMedicine
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Publication Info
- Year
- 2016
- Type
- preprint
- Volume
- 5
- Pages
- 182-182
- Citations
- 245
- Access
- Closed
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Cite This
Serena Liu,
Cole Trapnell
(2016).
Single-cell transcriptome sequencing: recent advances and remaining challenges.
F1000Research
, 5
, 182-182.
https://doi.org/10.12688/f1000research.7223.1
Identifiers
- DOI
- 10.12688/f1000research.7223.1