对基因本体术语进行分组以改进对微阵列数据中基因集富集的评估。
Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data.
作者信息
Lewin Alex, Grieve Ian C
机构信息
Department of Epidemiology and Public Health, Imperial College, Norfolk Place, London W2 1PG, UK.
出版信息
BMC Bioinformatics. 2006 Oct 3;7:426. doi: 10.1186/1471-2105-7-426.
BACKGROUND
Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find GO terms which are over-represented amongst the genes declared to be differentially expressed in the analysis of the microarray experiment. However, due to the high degree of dependence between GO terms, statistical testing is conservative, and interpretation is difficult.
RESULTS
We propose testing groups of GO terms rather than individual terms, to increase statistical power, reduce dependence between tests and improve the interpretation of results. We use the publicly available package POSOC to group the terms. Our method finds groups of GO terms significantly over-represented amongst differentially expressed genes which are not found by Fisher's tests on individual GO terms.
CONCLUSION
Grouping Gene Ontology terms improves the interpretation of gene set enrichment for microarray data.
背景
基因本体论（GO）术语常被用于评估微阵列实验的结果。最常见的做法是进行费舍尔精确检验，以找出在微阵列实验分析中被声明为差异表达的基因中过度富集的GO术语。然而，由于GO术语之间的高度依赖性，统计检验较为保守，且解释困难。
结果
我们建议对GO术语组而非单个术语进行检验，以提高统计功效，减少检验之间的依赖性并改善结果的解释。我们使用公开可用的软件包POSOC对术语进行分组。我们的方法发现了在差异表达基因中显著过度富集的GO术语组，而这些术语组在对单个GO术语进行费舍尔检验时并未被发现。
结论
对基因本体论术语进行分组可改善对微阵列数据的基因集富集情况的解释。
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