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ImmuneRegulation: a web-based tool for identifying human immune regulatory elements

机译:ImmuneRegulation:一种基于网络的工具用于识别人体免疫调节成分

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摘要

Humans vary considerably both in their baseline and activated immune phenotypes. We developed a user-friendly open-access web portal, ImmuneRegulation, that enables users to interactively explore immune regulatory elements that drive cell-type or cohort-specific gene expression levels. ImmuneRegulation currently provides the largest centrally integrated resource on human transcriptome regulation across whole blood and blood cell types, including (i) ∼43,000 genotyped individuals with associated gene expression data from ∼51,000 experiments, yielding genetic variant-gene expression associations on ∼220 million eQTLs; (ii) 14 million transcription factor (TF)-binding region hits extracted from 1945 ChIP-seq studies; and (iii) the latest GWAS catalog with 67,230 published variant-trait associations. Users can interactively explore associations between queried gene(s) and their regulators (cis-eQTLs, trans-eQTLs or TFs) across multiple cohorts and studies. These regulators may explain genotype-dependent gene expression variations and be critical in selecting the ideal cohorts or cell types for follow-up studies or in developing predictive models. Overall, ImmuneRegulation significantly lowers the barriers between complex immune regulation data and researchers who want rapid, intuitive and high-quality access to the effects of regulatory elements on gene expression in multiple studies to empower investigators in translating these rich data into biological insights and clinical applications, and is freely available at .
机译:人类的基线和激活的免疫表型差异很大。我们开发了一个用户友好的开放访问Web门户ImmuneRegulation,该门户使用户能够交互探索驱动细胞类型或特定人群基因表达水平的免疫调节元件。 ImmuneRegulation目前提供了跨全血和血细胞类型进行人类转录组调控的最大的中央整合资源,包括(i)约43,000个基因型个体,具有来自约51,000个实验的相关基因表达数据,在约2.2亿个eQTL上产生了遗传变异-基因表达关联; (ii)从1945年ChIP-seq研究中提取了1400万个转录因子(TF)结合区; (iii)最新的GWAS目录包含67,230个已发布的变异性状关联。用户可以在多个队列和研究中以交互方式探索所查询的基因与其调控因子(顺式eQTL,反式eQTL或TF)之间的关联。这些调节剂可以解释基因型依赖性基因表达的变化,对于选择理想的队列或细胞类型进行后续研究或建立预测模型至关重要。总体而言,ImmuneRegulation大大降低了复杂的免疫调节数据与希望快速,直观且高质量地获得调节元素对基因表达的影响的研究人员之间的障碍,从而使研究人员能够将丰富的数据转化为生物学见解和临床应用,可在上免费获得。

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