Challenges and emerging directions in single-cell analysis

被引：220

作者：

Yuan, Guo-Cheng ^{[1
,2
]}

Cai, Long ^{[3
]}

Elowitz, Michael ^{[4
]}

Enver, Tariq ^{[5
]}

Fan, Guoping ^{[6
]}

Guo, Guoji ^{[7
]}

Irizarry, Rafael ^{[1
,2
]}

Kharchenko, Peter ^{[8
]}

Kim, Junhyong ^{[9
]}

Orkin, Stuart ^{[10
,11
,12
]}

Quackenbush, John ^{[1
,2
]}

Saadatpour, Assieh ^{[1
,2
]}

Schroeder, Timm ^{[13
]}

Shivdasani, Ramesh ^{[14
]}

Tirosh, Itay ^{[15
]}

机构：

[1] Dana Farber Canc Inst, Dept Biostat & Computat Biol, Boston, MA 02115 USA

[2] Harvard TH Chan Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA

[3] CALTECH, Div Chem & Chem Engn, Pasadena, CA 91125 USA

[4] CALTECH, Div Biol & Biol Engn, Pasadena, CA 91125 USA

[5] UCL, Canc Inst, London, England

[6] Univ Calif Los Angeles, Dept Human Genet, Los Angeles, CA USA

[7] Zhejiang Univ, Ctr Stem Cell & Regenerat Med, Hangzhou, Zhejiang, Peoples R China

[8] Harvard Med Sch, Dept Biomed Informat, Boston, MA USA

[9] Univ Penn, Dept Biol, Philadelphia, PA 19104 USA

[10] Dana Farber Canc Inst, Dept Pediat Oncol, Boston, MA 02115 USA

[11] Boston Childrens Hosp, Div Hematol Oncol, Boston, MA USA

[12] Howard Hughes Med Inst, Boston, MA 02115 USA

[13] Swiss Fed Inst Technol, Dept Biosyst Sci & Engn, Basel, Switzerland

[14] Dana Farber Canc Inst, Dept Med Oncol, Boston, MA 02115 USA

[15] Broad Inst MIT & Harvard, Cambridge, MA USA

来源：

GENOME BIOLOGY | 2017年 / 18卷

关键词：

RNA-SEQUENCING REVEALS; GENE-EXPRESSION DATA; CHARACTERIZING HETEROGENEITY; COMPUTATIONAL ANALYSIS; SPATIAL-ORGANIZATION; TRANSCRIPTOME; GENOME; RECONSTRUCTION; LOCALIZATION; DISSECTION;

D O I：

10.1186/s13059-017-1218-y

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

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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