DRomics: A Turnkey Tool to Support the Use of the Dose-Response Framework for Omics Data in Ecological Risk Assessment
DRomics: A Turnkey Tool to Support the Use of the Dose-Response Framework for Omics Data in Ecological Risk Assessment
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DOI：
10.1021/acs.est.8b04752
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发表时间：
2018-12-18
影响因子：
11.4
通讯作者：
Delignette-Muller, Marie-Laure
中科院分区：
文献类型：
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作者：
Larras, Floriane;Billoir, Elise;Delignette-Muller, Marie-Laure
组学方法（例如转录组学、代谢组学）在生态风险评估（ERA）方面很有前景，因为它们提供了机制信息和早期预警信号。组学数据分析的关键步骤是浓度依赖性建模，其可能具有不同的趋势，包括单相（例如线性、指数）或双相（例如 U 形、钟形）形式。响应的多样性对显着响应的检测和建模以及效应浓度 (EC) 推导提出了挑战。此外，处理高通量数据集非常耗时，并且需要有效且自动化的处理例程。因此，我们开发了一种开源工具（DRomics，可作为 R 包和基于网络的服务使用），在消除不具有浓度依赖性和/或高变异性的分子反应（例如，微阵列中的基因表达）后，确定浓度-反应曲线描述的最佳模型。随后，从每条曲线估计 EC（例如，基准剂量），并根据曲线的模型参数对曲线进行分类。该工具特别致力于管理从实验设计中获得的数据，该实验设计有利于大量测试剂量而不是大量重复，并且还可以正确处理单相和双相趋势。该工具最终提供了结果表的恢复，可直接用于执行 ERA 方法。
Omics approaches (e.g., transcriptomics, metabolomics) are promising for ecological risk assessment (ERA) since they provide mechanistic information and early warning signals. A crucial step in the analysis of omics data is the modeling of concentration-dependency which may have different trends including monotonic (e.g., linear, exponential) or biphasic (e.g., U shape, bell shape) forms. The diversity of responses raises challenges concerning detection and modeling of significant responses and effect concentration (EC) derivation. Furthermore, handling high-throughput data sets is time-consuming and requires effective and automated processing routines. Thus, we developed an open source tool (DRomics, available as an R-package and as a web-based service) which, after elimination of molecular responses (e.g., gene expressions from microarrays) with no concentration-dependency and/or high variability, identifies the best model for concentration-response curve description. Subsequently, an EC (e.g., a benchmark dose) is estimated from each curve, and curves are classified based on their model parameters. This tool is especially dedicated to manage data obtained from an experimental design favoring a great number of tested doses rather than a great number of replicates and also to handle properly monotonic and biphasic trends. The tool finally provides restitution for a table of results that can be directly used to perform ERA approaches.