Challenges and emerging directions in single-cell analysis

Guo-Cheng Yuan^{1

2}, Long Cai³, Michael Elowitz⁴, Tariq Enver⁵, Guoping Fan⁶, Guoji Guo⁷, Rafael Irizarry^{8

9}, Peter Kharchenko¹⁰, Junhyong Kim¹¹, Stuart Orkin^{12

13

14}, John Quackenbush^{8

9}, Assieh Saadatpour^{8

9}, Timm Schroeder¹⁵, Ramesh Shivdasani¹⁶, Itay Tirosh¹⁷

Affiliations

¹ Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA. gcyuan@jimmy.harvard.edu.
² Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. gcyuan@jimmy.harvard.edu.
³ Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA.
⁴ Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
⁵ Cancer Institute, University College London, London, UK.
⁶ Department of Human Genetics, University of California, Los Angeles, CA, USA.
⁷ Center for Stem Cell and Regenerative Medicine, Zhejiang University, Hangzhou, China.
⁸ Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA.
⁹ Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
¹⁰ Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
¹¹ Department of Biology, University of Pennsylvania, Philadelphia, PA, USA.
¹² Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
¹³ Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA.
¹⁴ Howard Hughes Medical Institute, Boston, MA, USA.
¹⁵ Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
¹⁶ Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
¹⁷ Broad Institute of MIT and Harvard, Cambridge, MA, USA.

PMID: 28482897
PMCID: PMC5421338
DOI: 10.1186/s13059-017-1218-y

Review

Challenges and emerging directions in single-cell analysis

Guo-Cheng Yuan et al. Genome Biol. 2017.

. 2017 May 8;18(1):84.

doi: 10.1186/s13059-017-1218-y.

Authors

Affiliations

¹ Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA. gcyuan@jimmy.harvard.edu.
² Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. gcyuan@jimmy.harvard.edu.
³ Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA.
⁴ Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
⁵ Cancer Institute, University College London, London, UK.
⁶ Department of Human Genetics, University of California, Los Angeles, CA, USA.
⁷ Center for Stem Cell and Regenerative Medicine, Zhejiang University, Hangzhou, China.
⁸ Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA.
⁹ Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
¹⁰ Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
¹¹ Department of Biology, University of Pennsylvania, Philadelphia, PA, USA.
¹² Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
¹³ Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA.
¹⁴ Howard Hughes Medical Institute, Boston, MA, USA.
¹⁵ Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
¹⁶ Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
¹⁷ Broad Institute of MIT and Harvard, Cambridge, MA, USA.

PMID: 28482897
PMCID: PMC5421338
DOI: 10.1186/s13059-017-1218-y

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.

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References

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Challenges and emerging directions in single-cell analysis

Affiliations

Challenges and emerging directions in single-cell analysis

Authors

Affiliations

Abstract

References

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MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

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