MOTIVATION The analysis of dose-dependent effects on the gene expression is gaining attention in the field of toxicogenomics. Currently available computational methods are usually limited to specific omics platforms or biological annotations and are able to analyse only one experiment at a time. RESULTS We developed the software BMDx with a graphical user interface for the Benchmark Dose (BMD) analysis of transcriptomics data. We implemented an approach based on the fitting of multiple models and the selection of the optimal model based on the Akaike Information Criterion. The BMDx tool takes as an input a gene expression matrix and a phenotype table, computes the BMD, its related values, and IC50/EC50 estimations. It reports interactive tables and plots that the user can investigate for further details of the fitting, dose effects and functional enrichment. BMDx allows a fast and convenient comparison of the BMD values of a transcriptomics experiment at different time points and an effortless way to interpret the results. Furthermore, BMDx allows to analyse and to compare multiple experiments at once. AVAILABILITY AND IMPLEMENTATION BMDx is implemented as an R/Shiny software and is available at https://github.com/Greco-Lab/BMDx/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

中文翻译：

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BMDx：一个图形化Shiny应用程序，用于对转录组学数据进行基准剂量分析。

动机在毒理基因组学领域，对基因表达的剂量依赖性影响的分析日益受到关注。当前可用的计算方法通常仅限于特定的组学平台或生物学注释，并且一次只能分析一个实验。结果我们开发了具有图形用户界面的BMDx软件，用于转录组学数据的基准剂量（BMD）分析。我们实施了一种基于多个模型拟合的方法，并根据Akaike信息准则选择了最佳模型。BMDx工具将基因表达矩阵和表型表作为输入，计算BMD，其相关值以及IC50 / EC50估计值。它报告交互式表格和图解，用户可以调查以了解拟合的更多详细信息，剂量效应和功能丰富。BMDx可以快速方便地比较转录组学实验在不同时间点的BMD值，并且可以轻松地解释结果。此外，BMDx允许一次分析和比较多个实验。可用性和实现BMDx是作为R / Shiny软件实现的，可从https://github.com/Greco-Lab/BMDx/获得。补充信息补充数据可从Bioinformatics在线获得。可用性和实现BMDx是作为R / Shiny软件实现的，可从https://github.com/Greco-Lab/BMDx/获得。补充信息补充数据可从Bioinformatics在线获得。可用性和实现BMDx是作为R / Shiny软件实现的，可从https://github.com/Greco-Lab/BMDx/获得。补充信息补充数据可从Bioinformatics在线获得。