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Challenges and emerging directions in single-cell analysis

Yuan, Guo-Cheng and Cai, Long and Elowitz, Michael and Enver, Tariq and Fan, Guoping and Guo, Guoji and Irizarry, Rafael and Kharchenko, Peter and Kim, Junhyong and Orkin, Stuart and Quackenbush, John and Saadatpour, Assieh and Schroeder, Timm and Shivdasani, Ramesh and Tirosh, Itay (2017) Challenges and emerging directions in single-cell analysis. Genome Biology, 18 (1). Art. No. 84. ISSN 1474-760X. PMCID PMC5421338. https://resolver.caltech.edu/CaltechAUTHORS:20170515-103755842

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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.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1186/s13059-017-1218-yDOIArticle
http://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1218-yPublisherArticle
http://biorxiv.org/content/early/2017/04/15/127761OrganizationDiscussion Paper
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5421338/PubMed CentralArticle
ORCID:
AuthorORCID
Cai, Long0000-0002-7154-5361
Elowitz, Michael0000-0002-1221-0967
Additional Information:© 2017 The Author(s). 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. Received: 18 December 2016; Accepted: 21 April 2017; Published online: 08 May 2017. This article is a result of the discussions at the Radcliffe Institute Exploratory Seminar on “Theoretical Challenges in Single-Cell Analysis” in June 2016. We are grateful for the Radcliffe Institute’s generous financial and logistical support. The work was supported by a Radcliffe Institute Exploratory Seminar Award and by the NIH grants R13-CA124365 and R01-DK081113S1. Availability of data and materials: Not applicable. Authors’ contributions: GCY conceived the study. All authors participated in the discussions and writing of the manuscript. All authors read and approved the final manuscript. The authors declare that they have no competing interests. Ethics approval and consent to participate: Not applicable.
Funders:
Funding AgencyGrant Number
Radcliffe InstituteUNSPECIFIED
NIHR13-CA124365
NIHR01-DK081113S1
Issue or Number:1
PubMed Central ID:PMC5421338
Record Number:CaltechAUTHORS:20170515-103755842
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20170515-103755842
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:77447
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:16 May 2017 02:34
Last Modified:03 Oct 2019 17:57

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