A general modular framework for gene set enrichment analysis
A general modular framework for gene set enrichment analysis
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DOI：
10.1186/1471-2105-10-47
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发表时间：
2009-02-03
影响因子：
3
通讯作者：
Strimmer, Korbinian
中科院分区：
文献类型：
--
作者：
Ackermann, Marit;Strimmer, Korbinian
背景资料：在基因组研究中，基于基因集而不是单个基因的微阵列和其他高通量数据的分析变得越来越重要。相应地，大量的统计方法检测基因集富集已被提出，但各种方法的相互关系和相对性能仍然非常不清楚。结果：我们进行了广泛的调查基因集分析的统计方法，并确定一个共同的模块化结构的基础上最公布的方法。基于这一发现，我们提出了一个检测基因集富集的一般框架。这个框架提供了一个元理论的基因集分析，不仅有助于更好地了解每个嵌入式方法的相对优点，但也有利于原则性的比较，并提供了见解的相对相互作用的methods.Conclusion：我们使用这个框架进行计算机模拟比较261个不同的变种的基因集富集程序，并分析两个实验数据集。根据结果，我们提供了最佳实践的建议，选择有效的程序基因集富集分析。
Background: Analysis of microarray and other high-throughput data on the basis of gene sets, rather than individual genes, is becoming more important in genomic studies. Correspondingly, a large number of statistical approaches for detecting gene set enrichment have been proposed, but both the interrelations and the relative performance of the various methods are still very much unclear.Results: We conduct an extensive survey of statistical approaches for gene set analysis and identify a common modular structure underlying most published methods. Based on this finding we propose a general framework for detecting gene set enrichment. This framework provides a meta-theory of gene set analysis that not only helps to gain a better understanding of the relative merits of each embedded approach but also facilitates a principled comparison and offers insights into the relative interplay of the methods.Conclusion: We use this framework to conduct a computer simulation comparing 261 different variants of gene set enrichment procedures and to analyze two experimental data sets. Based on the results we offer recommendations for best practices regarding the choice of effective procedures for gene set enrichment analysis.