Design and computational analysis of single-cell RNA-sequencing experiments

被引:308
作者
Bacher, Rhonda [1 ]
Kendziorski, Christina [2 ]
机构
[1] Univ Wisconsin, Dept Stat, Madison, WI 53706 USA
[2] Univ Wisconsin, Dept Biostat & Med Informat, Madison, WI 53726 USA
来源
GENOME BIOLOGY | 2016年 / 17卷
关键词
GENE-EXPRESSION; DIFFERENTIAL EXPRESSION; SEQ DATA; QUALITY-CONTROL; TRANSCRIPTIONAL HETEROGENEITY; NORMALIZATION; FRAMEWORK; NOISE; QUANTIFICATION; RECONSTRUCTION;
D O I
10.1186/s13059-016-0927-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 RNA-sequencing (scRNA-seq) has emerged as a revolutionary tool that allows us to address scientific questions that eluded examination just a few years ago. With the advantages of scRNA-seq come computational challenges that are just beginning to be addressed. In this article, we highlight the computational methods available for the design and analysis of scRNA-seq experiments, their advantages and disadvantages in various settings, the open questions for which novel methods are needed, and expected future developments in this exciting area.
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页数:14
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