Revisiting Global Gene Expression Analysis

被引：430
作者：
Loven, Jakob [1 ]
Orlando, David A. [1 ]
Sigova, Alla A. [1 ]
Lin, Charles Y. [1 ,2 ]
Rahl, Peter B. [1 ]
Burge, Christopher B. [3 ]
Levens, David L. [4 ]
Lee, Tong Ihn [1 ]
Young, Richard A. [1 ,3 ]
机构：
[1] Whitehead Inst Biomed Res, Cambridge, MA 02142 USA
[2] MIT, Computat & Syst Biol Program, Cambridge, MA 02139 USA
[3] MIT, Dept Biol, Cambridge, MA 02139 USA
[4] NCI, Gene Regulat Sect, Pathol Lab, Ctr Canc Res, Bethesda, MD 20892 USA
来源：
CELL | 2012年 / 151卷 / 03期
基金：
美国国家卫生研究院; 瑞典研究理事会;
关键词：
C-MYC; MOLECULAR CLASSIFICATION; BREAST-CANCER; RNA-SEQ; NORMALIZATION; ARRAYS; PREDICTION; DISCOVERY; ADENOCARCINOMA; MICROARRAYS;
D O I：
10.1016/j.cell.2012.10.012
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：
Gene expression analysis is a widely used and powerful method for investigating the transcriptional behavior of biological systems, for classifying cell states in disease, and for many other purposes. Recent studies indicate that common assumptions currently embedded in experimental and analytical practices can lead to misinterpretation of global gene expression data. We discuss these assumptions and describe solutions that should minimize erroneous interpretation of gene expression data from multiple analysis platforms.
引用
收藏
页码：476 / 482
页数：7
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