Gene set enrichment analysis: performance evaluation and usage guidelines

被引:166
|
作者
Hung, Jui-Hung [1 ]
Yang, Tun-Hsiang [1 ]
Hu, Zhenjun [1 ]
Weng, Zhiping [1 ]
DeLisi, Charles [1 ]
机构
[1] Boston Univ, Bioinformat Program, Boston, MA 02215 USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
gene set enrichment analysis; pathway enrichment analysis; expression analysis; GSEA; PWEA; performance evaluation; controlled mutual coverage; CMC; FALSE DISCOVERY RATE; MICROARRAY DATA; METABOLIC PATHWAYS; EXPRESSION DATA; NORMALIZATION; IDENTIFICATION; PROBESETS; SUMMARIES; VALUES; ARRAY;
D O I
10.1093/bib/bbr049
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
A central goal of biology is understanding and describing the molecular basis of plasticity: the sets of genes that are combinatorially selected by exogenous and endogenous environmental changes, and the relations among the genes. The most viable current approach to this problem consists of determining whether sets of genes are connected by some common theme, e.g. genes from the same pathway are overrepresented among those whose differential expression in response to a perturbation is most pronounced. There are many approaches to this problem, and the results they produce show a fair amount of dispersion, but they all fall within a common framework consisting of a few basic components. We critically review these components, suggest best practices for carrying out each step, and propose a voting method for meeting the challenge of assessing different methods on a large number of experimental data sets in the absence of a gold standard.
引用
收藏
页码:281 / 291
页数:11
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