{"title":"微阵列数据的综合分析:系统毒理学的路径","authors":"A. Rasche, R. Yildirimman, R. Herwig","doi":"10.1002/9780470744307.GAT207","DOIUrl":null,"url":null,"abstract":"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. \n \n \nKeywords: \n \nAffymetrix GeneChip; \nhigh-throughput data storage; \nmeta-analysis; \nmicroarray","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Integrative Analysis of Microarray Data: A Path for Systems Toxicology\",\"authors\":\"A. Rasche, R. Yildirimman, R. Herwig\",\"doi\":\"10.1002/9780470744307.GAT207\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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. \\n \\n \\nKeywords: \\n \\nAffymetrix GeneChip; \\nhigh-throughput data storage; \\nmeta-analysis; \\nmicroarray\",\"PeriodicalId\":325382,\"journal\":{\"name\":\"General, Applied and Systems Toxicology\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"General, Applied and Systems Toxicology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/9780470744307.GAT207\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"General, Applied and Systems Toxicology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/9780470744307.GAT207","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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