DrugMatrix is a valuable toxicogenomic dataset, which provides in vivo transcriptome data corresponding to hundreds of chemical drugs. However, the relationships between drugs and how those drugs affect the biological process are still unknown. The high dimensionality of the microarray data hinders its application. The aims of this study are to (1) represent the transcriptome data by lower-dimensional vectors, (2) compare drug similarity, (3) represent drug combinations by adding vectors and (4) infer drug mechanism of action (MoA) and genotoxicity features. We borrowed the latent semantic analysis (LSA) technique from natural language processing to represent treatments (drugs with multiple concentrations and time points) by dense vectors, each dimension of which is an orthogonal biological feature. The gProfiler enrichment tool was used for the 100-dimensional vector feature annotation. The similarity between treatments vectors was calculated by the cosine function. Adding vectors may represent drug combinations, treatment times or treatment doses that are not presented in the original data. Drug–drug interaction pairs had a higher similarity than random drug pairs in the hepatocyte data. The vector features helped to reveal the MoA. Differential feature expression was also implicated for genotoxic and non-genotoxic carcinogens. An easy-to-use Web tool was developed by Shiny Web application framework for the exploration of treatment similarities and drug combinations (https://bioinformatics.fafu.edu.cn/drugmatrix/). We represented treatments by vectors and provided a tool that is useful for hypothesis generation in toxicogenomic, such as drug similarity, drug repurposing, combination therapy and MoA.

DrugMatrix是有价值的毒物基因组数据集，可提供对应于数百种化学药物的体内转录组数据。但是，药物之间的关系以及这些药物如何影响生物过程仍然未知。微阵列数据的高维度阻碍了其应用。这项研究的目的是（1）通过低维向量表示转录组数据，（2）比较药物相似性，（3）通过添加向量表示药物组合，以及（4）推断药物的作用机理（MoA）和遗传毒性特征。我们从自然语言处理中借用了潜在语义分析（LSA）技术，通过密集的矢量表示治疗（具有多个浓度和时间点的药物），每个矢量的维度都是正交的生物学特征。gProfiler富集工具用于100维矢量特征注释。通过余弦函数计算处理向量之间的相似性。添加的载体可能代表原始数据中未列出的药物组合，治疗时间或治疗剂量。在肝细胞数据中，药物-药物相互作用对比随机药物对具有更高的相似性。矢量特征有助于揭示MoA。差异特征表达也涉及遗传毒性和非遗传毒性致癌物。Shiny Web应用程序框架开发了一种易于使用的Web工具，用于探索治疗相似性和药物组合（https://bioinformatics.fafu.edu.cn/drugmatrix/）。我们用载体代表了治疗方法，并提供了可用于产生毒物基因组学假设的工具，