首页> 美国卫生研究院文献>Proceedings of the National Academy of Sciences of the United States of America >PNAS Plus: Immuno-Navigator a batch-corrected coexpression database reveals cell type-specific gene networks in the immune system
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PNAS Plus: Immuno-Navigator a batch-corrected coexpression database reveals cell type-specific gene networks in the immune system

机译:PNAS Plus:Immuno-Navigator经过批处理校正的共表达数据库揭示了免疫系统中特定于细胞类型的基因网络

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摘要

High-throughput gene expression data are one of the primary resources for exploring complex intracellular dynamics in modern biology. The integration of large amounts of public data may allow us to examine general dynamical relationships between regulators and target genes. However, obstacles for such analyses are study-specific biases or batch effects in the original data. Here we present Immuno-Navigator, a batch-corrected gene expression and coexpression database for 24 cell types of the mouse immune system. We systematically removed batch effects from the underlying gene expression data and showed that this removal considerably improved the consistency between inferred correlations and prior knowledge. The data revealed widespread cell type-specific correlation of expression. Integrated analysis tools allow users to use this correlation of expression for the generation of hypotheses about biological networks and candidate regulators in specific cell types. We show several applications of Immuno-Navigator as examples. In one application we successfully predicted known regulators of importance in naturally occurring Treg cells from their expression correlation with a set of Treg-specific genes. For one high-scoring gene, integrin β8 (Itgb8), we confirmed an association between Itgb8 expression in forkhead box P3 (Foxp3)-positive T cells and Treg-specific epigenetic remodeling. Our results also suggest that the regulation of Treg-specific genes within Treg cells is relatively independent of Foxp3 expression, supporting recent results pointing to a Foxp3-independent component in the development of Treg cells.
机译:高通量基因表达数据是探索现代生物学中复杂细胞内动力学的主要资源之一。大量公共数据的整合可能使我们可以检查调节剂与靶基因之间的一般动力学关系。但是,此类分析的障碍是研究特定的偏见或原始数据中的批次效应。在这里,我们介绍了Immuno-Navigator,这是一种针对24种细胞类型的小鼠免疫系统的批处理校正的基因表达和共表达数据库。我们从潜在的基因表达数据中系统地删除了批处理效应,并表明该删除显着提高了推断的相关性和先验知识之间的一致性。数据揭示了广泛的细胞类型特异性表达相关性。集成的分析工具允许用户使用表达的这种相关性来生成有关特定细胞类型中的生物网络和候选调控因子的假设。我们以Immuno-Navigator的几种应用为例。在一个应用中,我们成功地从自然表达的Treg细胞与一组Treg特异性基因的表达相关性中预测了重要的调节剂。对于一个高分基因,整合素β8(Itgb8),我们证实了叉头盒P3(Foxp3)阳性T细胞中Itgb8表达与Treg特异性表观遗传重塑之间存在关联。我们的研究结果还表明,Treg细胞内Treg特异性基因的调节相对独立于Foxp3表达,支持最近的研究结果指出了Treg细胞发育中的Foxp3独立成分。

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