gomafunctionalenrichmentanalysistoolbasedongomodules

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	gomafunctionalenrichmentanalysistoolbasedongomodules
	Huang Qiang; Wu Lingyun; Wang Yong; Zhang Xiangsun
	2013-01-01
发表期刊	chinesejournalofcancer
ISSN	1000-467X
卷号	32 期号:4 页码:195
摘要	Analyzing the function of gene sets is a critical step in interpreting the results of high-throughput experiments in systems biology. A variety of enrichment analysis tools have been developed in recent years, but most output a long list of significantly enriched terms that are often redundant, making it difficult to extract the most meaningful functions. In this paper, we present GOMA, a novel enrichment analysis method based on the new concept of enriched functional Gene Ontology (GO) modules. With this method, we systematically revealed functional GO modules, i.e., groups of functionally similar GO terms, via an optimization model and then ranked them by enrichment scores. Our new method simplifies enrichment analysis results by reducing redundancy, thereby preventing inconsistent enrichment results among functionally similar terms and providing more biologically meaningful results.
语种	英语
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/49424
专题	应用数学研究所
作者单位	中国科学院数学与系统科学研究院
推荐引用方式 GB/T 7714	Huang Qiang,Wu Lingyun,Wang Yong,et al. gomafunctionalenrichmentanalysistoolbasedongomodules[J]. chinesejournalofcancer,2013,32(4):195.
APA	Huang Qiang,Wu Lingyun,Wang Yong,&Zhang Xiangsun.(2013).gomafunctionalenrichmentanalysistoolbasedongomodules.chinesejournalofcancer,32(4),195.
MLA	Huang Qiang,et al."gomafunctionalenrichmentanalysistoolbasedongomodules".chinesejournalofcancer 32.4(2013):195.