Delineating biological and technical variance in single cell expression data

被引：15
作者：
Arzalluz-Luque, Angeles [3 ]
Devailly, Guillaume [1 ,2 ]
Mantsoki, Anna [1 ,2 ]
Joshi, Anagha [1 ,2 ]
机构：
[1] Univ Edinburgh, Div Dev Biol, Roslin Inst, Easter Bush Campus, Roslin EH25 9RG, Midlothian, Scotland
[2] Univ Edinburgh, Royal Dick Sch Vet Studies, Easter Bush Campus, Roslin EH25 9RG, Midlothian, Scotland
[3] CIPF, Genom Gene Express Lab, Carrer dEduardo Primo Yufera 3, Valencia 46012, Spain
来源：
INTERNATIONAL JOURNAL OF BIOCHEMISTRY & CELL BIOLOGY | 2017年 / 90卷
基金：
英国生物技术与生命科学研究理事会;
关键词：
Single cell; RNA-seq; Noise; Variability; EMBRYONIC STEM-CELLS; RNA-SEQ EXPERIMENTS; GENE-EXPRESSION; MESSENGER-RNA; TUMOR-CELLS; TRANSCRIPTOMICS; HETEROGENEITY; NOISE; REVEALS;
D O I：
10.1016/j.biocel.2017.07.006
中图分类号：
Q5 [生物化学]; Q7 [分子生物学];
学科分类号：
071010 ; 081704 ;
摘要：
Single cell transcriptomics is becoming a common technique to unravel new biological phenomena whose functional significance can only be understood in the light of differences in gene expression between single cells. The technology is still in its early days and therefore suffers from many technical challenges. This review discusses the continuous effort to identify and systematically characterise various sources of technical variability in single cell expression data and the need to further develop experimental and computational tools and resources to help deal with it.
引用
收藏
页码：161 / 166
页数：6
相关论文
共 40 条
[1]   METHOD FOR DETECTION OF SPECIFIC RNAS IN AGAROSE GELS BY TRANSFER TO DIAZOBENZYLOXYMETHYL-PAPER AND HYBRIDIZATION WITH DNA PROBES [J].
ALWINE, JC ;
KEMP, DJ ;
STARK, GR .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 1977, 74 (12) :5350-5354
[2]   Design and computational analysis of single-cell RNA-sequencing experiments [J].
Bacher, Rhonda ;
Kendziorski, Christina .
GENOME BIOLOGY, 2016, 17
[3]  
Brennecke P, 2013, NAT METHODS, V10, P1093, DOI [10.1038/nmeth.2645, 10.1038/NMETH.2645]
[4]   Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells [J].
Buettner, Florian ;
Natarajan, Kedar N. ;
Casale, F. Paolo ;
Proserpio, Valentina ;
Scialdone, Antonio ;
Theis, Fabian J. ;
Teichmann, Sarah A. ;
Marioni, John C. ;
Stegie, Oliver .
NATURE BIOTECHNOLOGY, 2015, 33 (02) :155-160
[5]   Spatiotemporal transcriptomics reveals the evolutionary history of the endoderm germ layer [J].
Hashimshony, Tamar ;
Feder, Martin ;
Levin, Michal ;
Hall, Brian K. ;
Yanai, Itai .
NATURE, 2015, 519 (7542) :219-+
[6]  
Hicks S. C., 2017, MISSING DATA TECHNIC
[7]   Classification of low quality cells from single-cell RNA-seq data [J].
Ilicic, Tomislav ;
Kim, Jong Kyoung ;
Kolodziejczyk, Aleksandra A. ;
Bagger, Frederik Otzen ;
McCarthy, Davis James ;
Marioni, John C. ;
Teichmann, Sarah A. .
GENOME BIOLOGY, 2016, 17
[8]   Representation is faithfully preserved in global cDNA amplified exponentially from sub-picogram quantities of mRNA [J].
Iscove, NN ;
Barbara, M ;
Gu, M ;
Gibson, M ;
Modi, C ;
Winegarden, N .
NATURE BIOTECHNOLOGY, 2002, 20 (09) :940-943
[9]  
Islam S, 2014, NAT METHODS, V11, P163, DOI [10.1038/NMETH.2772, 10.1038/nmeth.2772]
[10]   Synthetic spike-in standards for RNA-seq experiments [J].
Jiang, Lichun ;
Schlesinger, Felix ;
Davis, Carrie A. ;
Zhang, Yu ;
Li, Renhua ;
Salit, Marc ;
Gingeras, Thomas R. ;
Oliver, Brian .
GENOME RESEARCH, 2011, 21 (09) :1543-1551
1234