Faculty of Medicine and Health Technology, Tampere University, Tampere 33100, Finland.
BioMediTech Institute, Tampere University, Tampere 33100, Finland.
Bioinformatics. 2020 May 1;36(9):2932-2933. doi: 10.1093/bioinformatics/btaa030.
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.
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.
BMDx is implemented as an R/Shiny software and is available at https://github.com/Greco-Lab/BMDx/.
Supplementary data are available at Bioinformatics online.
在毒理基因组学领域，分析剂量依赖性对基因表达的影响正受到关注。目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。
我们开发了一个名为 BMDx 的软件，它具有用于转录组数据分析的基准剂量（BMD）分析的图形用户界面。我们实现了一种基于拟合多个模型并根据赤池信息量准则选择最佳模型的方法。BMDx 工具将基因表达矩阵和表型表作为输入，计算 BMD 及其相关值以及 IC50/EC50 估计值。它报告交互式表格和图形，用户可以调查拟合、剂量效应和功能富集的详细信息。BMDx 允许快速方便地比较不同时间点转录组实验的 BMD 值，并轻松解释结果。此外，BMDx 允许一次分析和比较多个实验。
BMDx 作为 R/Shiny 软件实现，并可在 https://github.com/Greco-Lab/BMDx/ 上获得。
补充数据可在 Bioinformatics 在线获得。
