基因表达谱富集分析方法研究进展

Progress on Enrichment Analysis Approach of Gene Expression Profiles

微阵列技术是生物技术变革的核心,允许研究者同时监测成千上万个基因的表达水平,已广泛应用于医学研究。如何挖掘海量基因表达信息中的有用信息并进行生物学专业解释,是基因表达谱数据分析领域所面临的一个重要挑战。不同的研究者提出了各种基于基因集进行富集分析的方法,在此将这些方法大致分为两大类,即bottom-up方法和top-down方法。前者先进行单基因分析,然后根据生物学领域知识注释基因集并进行分析。该方法应用广泛,且结果比单基因分析容易解释。后者先根据生物学领域知识将各基因进行归类,然后进行基因差异表达模式分析。该方法不仅能提高结论的可解释性,而且能达到降维的目的。

Microarrays are at the center of a revolution in biotechnology, allowing researchers to simultaneously monitor the expression of tens of thousands of genes, having been widely used in medical research. The main challenge faced by the researchers is to extract useful information from such gene expression profiles and then implement biological interpreta- tion of such results. At present, all kinds of different research groups based on pre-defined gene set proposed different enrichment analysis methods. In this paper, these methods will be roughly divided into two categories： bottom-up approach and top-down approach. The former approach tested genes individually first then aggregated by biological knowledge. This approach was widely used, and its results were easier to explain than the results of the single gene analysis. The latter approach performed domain aggregation by first combining gene expressions before testing for differentially expressed patterns. This method can not only increase interpretability of analysis output, but also reach dimension reduction purposes.