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Disease and phenotype gene set analysis of disease-based gene expression in mouse and human

机译:小鼠和人类基于疾病的基因表达的疾病和表型基因组分析

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摘要

The genetic contributions to common disease and complex disease phenotypes are pleiotropic, multifactorial, and combinatorial. Gene set analysis is a computational approach used in the analysis of microarray data to rapidly query gene combinations and multifactorial processes. Here we use novel gene sets based on population-based human genetic associations in common human disease or experimental genetic mouse models to analyze disease-related microarray studies. We developed a web-based analysis tool that uses these novel disease- and phenotype-related gene sets to analyze microarray-based gene expression data. These gene sets show disease and phenotype specificity in a species-specific and cross-species fashion. In this way, we integrate population-based common human disease genetics, mouse genetically determined phenotypes, and disease or phenotype structured ontologies, with gene expression studies relevant to human disease. This may aid in the translation of large-scale high-throughput datasets into the context of clinically relevant disease phenotypes.
机译:对常见疾病和复杂疾病表型的遗传贡献是多效性,多因素和组合性的。基因组分析是一种用于微阵列数据分析的计算方法,可以快速查询基因组合和多因素过程。在这里,我们使用基于常见人类疾病或实验性遗传小鼠模型中基于人群的人类遗传协会的新颖基因集来分析与疾病相关的微阵列研究。我们开发了基于网络的分析工具,该工具使用这些新颖的疾病和与表型相关的基因集来分析基于微阵列的基因表达数据。这些基因组以物种特异性和跨物种的方式显示疾病和表型特异性。通过这种方式,我们将基于人群的常见人类疾病遗传学,小鼠遗传确定的表型以及疾病或表型结构化本体与人类疾病相关的基因表达研究相结合。这可能有助于将大规模高通量数据集转换为临床相关疾病表型的背景。

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