微阵列数据的综合分析:系统毒理学的路径

A. Rasche, R. Yildirimman, R. Herwig
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引用次数: 2

摘要

微阵列是基因表达全基因组分析的标准工具。例如,存在多种研究,跟踪系统在复合治疗方面的变化,或比较治疗与未治疗状态。除了这些单一研究之外,并行分析许多此类研究的综合方法也越来越受到关注,因为它们构成了识别与被分析系统相关的一般生物过程的关键步骤,因此将导致识别更稳定和健壮的标记基因。对于基因表达分析,Affymetrix阵列是一种成熟且广泛使用的实验系统。在本章中,我们提供了对这种微阵列技术的基本了解,并描述了数据的设计,预处理和分析。标准化和自动化的预处理程序对于许多数据集的后续并行分析至关重要。这些程序得到了存储和信息系统的极大支持,这些存储和信息系统收集了必要的信息。作为对大量毒理学数据集进行综合分析的一个例子,我们描述了结合不同芯片平台、不同物种以及不同基因毒性和非基因毒性化合物治疗的荟萃分析的最新结果。我们展示了如何通过这种方法重建毒性的一般机制,生物学途径和终点。关键词:Affymetrix基因芯片;高通量数据存储;荟萃分析;微阵列
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Integrative Analysis of Microarray Data: A Path for Systems Toxicology
Microarrays are the standard tool for a genome-wide analysis of gene expression. Multiple studies exist that, for example, track changes of systems with respect to compound treatment or compare the treated versus the untreated states. Besides these single studies, integrative approaches that analyze many such studies in parallel have gained increasing attention because they constitute a crucial step for the identification of general biological processes to relevant the system under analysis and would, thus, lead to the identification of more stable and robust marker genes. For gene expression analysis, the Affymetrix arrays are a well-established and widely used experimental system. In this chapter, we provide a basic understanding of this microarray technology and describe the design, pre-processing, and analysis of the data. Standardized and automatic pre-processing procedures are essential for the subsequent parallel analysis of many data sets. These procedures are greatly supported by storage and information systems collecting the essential information. As an example for an integrated analysis of a large number of toxicology data sets, we describe recent results on a meta-analysis combining different chip platforms, different species, and treatments with different genotoxic and non-genotoxic compounds. We show how general mechanisms, biological pathways, and endpoints of toxicity can be reconstructed by this approach. Keywords: Affymetrix GeneChip; high-throughput data storage; meta-analysis; microarray
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