Transcriptional switch (TS) is a widely observed phenomenon caused by changes in the relative expression of transcripts from the same gene, in spatial, temporal or other dimensions. TS has been associated with human diseases, plant development and stress responses. Its investigation is often hampered by a lack of suitable tools allowing comprehensive and flexible TS analysis for high-throughput RNA sequencing (RNA-Seq) data. Here, we present deepTS, a user-friendly web-based implementation that enables a fully interactive, multifunctional identification, visualization and analysis of TS events for large-scale RNA-Seq datasets from pairwise, temporal and population experiments. deepTS offers rich functionality to streamline RNA-Seq-based TS analysis for both model and non-model organisms and for those with or without reference transcriptome. The presented case studies highlight the capabilities of deepTS and demonstrate its potential for the transcriptome-wide TS analysis of pairwise, temporal and population RNA-Seq data. We believe deepTS will help research groups, regardless of their informatics expertise, perform accessible, reproducible and collaborative TS analyses of large-scale RNA-Seq data.

中文翻译：

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使用 deepTS 从成对、时间和群体 RNA-Seq 数据探索转录转换。

转录转换 (TS) 是一种广泛观察到的现象，由来自同一基因的转录本在空间、时间或其他维度上的相对表达的变化引起。TS 与人类疾病、植物发育和应激反应有关。由于缺乏合适的工具，可以对高通量 RNA 测序 (RNA-Seq) 数据进行全面和灵活的 TS 分析，因此其调查常常受到阻碍。在这里，我们介绍了 deepTS，这是一种用户友好的基于 Web 的实现，它能够对来自成对、时间和群体实验的大规模 RNA-Seq 数据集的 TS 事件进行完全交互式、多功能的识别、可视化和分析。deepTS 提供了丰富的功能，可以简化模型和非模型生物以及具有或不具有参考转录组的生物的基于 RNA-Seq 的 TS 分析。所呈现的案例研究突出了 deepTS 的功能，并证明了其在对成对、时间和群体 RNA-Seq 数据进行全转录组 TS 分析方面的潜力。我们相信 deepTS 将帮助研究小组，无论他们的信息学专业知识如何，对大规模 RNA-Seq 数据进行可访问、可重复和协作的 TS 分析。