PAGE: Parametric analysis of gene set enrichment
PAGE: Parametric analysis of gene set enrichment
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DOI：
10.1186/1471-2105-6-144
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发表时间：
2005-06-08
影响因子：
3
通讯作者：
Volsky, DJ
中科院分区：
文献类型：
--
作者：
Kim, SY;Volsky, DJ
背景资料：基因集富集分析（GSEA）是一种微阵列数据分析方法，其使用预定义的基因集和基因等级来识别微阵列数据集中的显著生物学变化。GSEA是特别有用的基因表达变化时，在一个给定的微阵列dataset.Results的变化是最小或medium.Results：我们开发了一种改进的基因集富集分析方法的基础上的参数统计分析模型。与GSEA相比，基因集富集的参数分析（PAGE）检测到大量显著改变的基因集，其p值低于GSEA计算的相应p值。因为PAGE使用正态分布进行统计推断，所以它需要比GSEA更少的计算，GSEA需要对置换数据集进行重复计算。PAGE能够从微阵列数据中检测到显著改变的基因组，而与不同的Affyssin探针水平分析方法或不同的微阵列平台无关。结论：PAGE技术在基因组水平上的敏感性高于GSEA技术，且计算量明显低于GSEA技术，可以从基因芯片数据中识别出发生显著变化的生物学主题，适用于多个基因芯片数据的比较。我们提供PAGE作为一种有用的微阵列分析方法。
Background: Gene set enrichment analysis (GSEA) is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes in microarray data sets. GSEA is especially useful when gene expression changes in a given microarray data set is minimal or moderate.Results: We developed a modified gene set enrichment analysis method based on a parametric statistical analysis model. Compared with GSEA, the parametric analysis of gene set enrichment ( PAGE) detected a larger number of significantly altered gene sets and their p-values were lower than the corresponding p-values calculated by GSEA. Because PAGE uses normal distribution for statistical inference, it requires less computation than GSEA, which needs repeated computation of the permutated data set. PAGE was able to detect significantly changed gene sets from microarray data irrespective of different Affymetrix probe level analysis methods or different microarray platforms. Comparison of two aged muscle microarray data sets at gene set level using PAGE revealed common biological themes better than comparison at individual gene level.Conclusion: PAGE was statistically more sensitive and required much less computational effort than GSEA, it could identify significantly changed biological themes from microarray data irrespective of analysis methods or microarray platforms, and it was useful in comparison of multiple microarray data sets. We offer PAGE as a useful microarray analysis method.