Yuan, G-C;
Cai, L;
Elowitz, M;
Enver, T;
Fan, G;
Guo, G;
Irizarry, R;
... Tirosh, I; + view all
(2017)
Challenges and emerging directions in single-cell analysis.
Genome Biology
, 18
, Article 84. 10.1186/s13059-017-1218-y.
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Abstract
Single-cell analysis is a rapidly evolving approach to characterize genome-scale molecular information at the individual cell level. Development of single-cell technologies and computational methods has enabled systematic investigation of cellular heterogeneity in a wide range of tissues and cell populations, yielding fresh insights into the composition, dynamics, and regulatory mechanisms of cell states in development and disease. Despite substantial advances, significant challenges remain in the analysis, integration, and interpretation of single-cell omics data. Here, we discuss the state of the field and recent advances and look to future opportunities.
| Type: | Article |
|---|---|
| Title: | Challenges and emerging directions in single-cell analysis |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1186/s13059-017-1218-y |
| Publisher version: | https://doi.org/10.1186/s13059-017-1218-y |
| Language: | English |
| Additional information: | © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
| Keywords: | Science & Technology, Life Sciences & Biomedicine, Biotechnology & Applied Microbiology, Genetics & Heredity, Rna-Sequencing Reveals, Gene-Expression Data, In-Situ, Characterizing Heterogeneity, Epigenetic Heterogeneity, Computational Analysis, Spatial-Organization, SEQ, Transcriptome, Genome |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute > Research Department of Cancer Bio |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10038302 |
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