SUMMARY Genomics has dramatically improved our understanding of the molecular origins of certain human diseases. Nonetheless, our health is also influenced by the cumulative impact of exposures experienced across the life course (termed 'exposome'). The study of the high-dimensional exposome offers a new paradigm for investigating environmental contributions to disease etiology. However, there is a lack of bioinformatics tools for managing, visualizing and analyzing the exposome. The analysis data should include both association with health outcomes and integration with omic layers. We provide a generic framework called rexposome project, developed in the R/Bioconductor architecture that includes object-oriented classes and methods to leverage high-dimensional exposome data in disease association studies including its integration with a variety of high-throughput data types. The usefulness of the package is illustrated by analyzing a real dataset including exposome data, three health outcomes related to respiratory diseases and its integration with the transcriptome and methylome. AVAILABILITY AND IMPLEMENTATION rexposome project is available at https://isglobal-brge.github.io/rexposome/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

中文翻译：

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使用Rexposome Bioconductor套件对暴露体和组学数据进行全面研究。

小结基因组学极大地改善了我们对某些人类疾病的分子起源的理解。但是，我们的健康也受到整个生命过程中暴露的累积影响的影响（称为“暴露”）。高维暴露体的研究为研究环境对疾病病因的贡献提供了新的范例。但是，缺乏用于管理，可视化和分析暴露体的生物信息学工具。分析数据应既包括与健康结果的关联，也包括与眼压层的整合。我们提供了一个称为rexposome项目的通用框架，在R / Bioconductor架构中开发，包括面向对象的类和方法，以在疾病关联研究中利用高维暴露数据，包括与各种高通量数据类型的集成。通过分析包括暴露数据，与呼吸系统疾病相关的三个健康结局及其与转录组和甲基化组的整合的真实数据集，说明了该软件包的有用性。可用性和实现rexposome项目可从https://isglobal-brge.github.io/rexposome/获得。补充信息补充数据可从Bioinformatics在线获得。与呼吸系统疾病有关的三个健康结局及其与转录组和甲基化组的整合。可用性和实现rexposome项目可从https://isglobal-brge.github.io/rexposome/获得。补充信息补充数据可从Bioinformatics在线获得。与呼吸系统疾病有关的三个健康结局及其与转录组和甲基化组的整合。可用性和实现rexposome项目可从https://isglobal-brge.github.io/rexposome/获得。补充信息补充数据可从Bioinformatics在线获得。