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首页> 外文期刊>BMC Genomics >Microarray data integration for genome-wide analysis of human tissue-selective gene expression
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Microarray data integration for genome-wide analysis of human tissue-selective gene expression

机译：基因芯片数据整合，用于全基因组人类组织选择性基因表达分析

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BackgroundMicroarray gene expression data are accumulating in public databases. The expression profiles contain valuable information for understanding human gene expression patterns. However, the effective use of public microarray data requires integrating the expression profiles from heterogeneous sources.ResultsIn this study, we have compiled a compendium of microarray expression profiles of various human tissue samples. The microarray raw data generated in different research laboratories have been obtained and combined into a single dataset after data normalization and transformation. To demonstrate the usefulness of the integrated microarray data for studying human gene expression patterns, we have analyzed the dataset to identify potential tissue-selective genes. A new method has been proposed for genome-wide identification of tissue-selective gene targets using both microarray intensity values and detection calls. The candidate genes for brain, liver and testis-selective expression have been examined, and the results suggest that our approach can select some interesting gene targets for further experimental studies.ConclusionA computational approach has been developed in this study for combining microarray expression profiles from heterogeneous sources. The integrated microarray data can be used to investigate tissue-selective expression patterns of human genes.
机译：背景微阵列基因表达数据正在公共数据库中积累。表达谱包含用于理解人类基因表达模式的有价值的信息。然而，有效利用公共微阵列数据需要整合来自不同来源的表达谱。结果在本研究中，我们汇编了各种人体组织样品的微阵列表达谱纲要。已获得在不同研究实验室中生成的微阵列原始数据，并在数据归一化和转换后将其组合到单个数据集中。为了证明整合的微阵列数据对研究人类基因表达模式的有用性，我们分析了数据集以鉴定潜在的组织选择性基因。已经提出了一种使用微阵列强度值和检测调用对组织选择性基因靶标进行全基因组鉴定的新方法。对大脑，肝脏和睾丸选择性表达的候选基因进行了研究，结果表明我们的方法可以选择一些有趣的基因靶点，以进行进一步的实验研究。资料来源。整合的微阵列数据可用于研究人类基因的组织选择性表达模式。

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