Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China.
College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
Bioinformatics. 2023 Jan 1;39(1). doi: 10.1093/bioinformatics/btac777.
With the continuous development of high-throughput sequencing technology, bioinformatic analysis of omics data plays an increasingly important role in life science research. Many R packages are widely used for omics analysis, such as DESeq2, clusterProfiler and STRINGdb. And some online tools based on them have been developed to free bench scientists from programming with these R packages. However, the charts generated by these tools are usually in a fixed, non-editable format and often fail to clearly demonstrate the details the researchers intend to express. To address these issues, we have created Visual Omics, an online tool for omics data analysis and scientific chart editing. Visual Omics integrates multiple omics analyses which include differential expression analysis, enrichment analysis, protein domain prediction and protein-protein interaction analysis with extensive graph presentations. It can also independently plot and customize basic charts that are involved in omics analysis, such as various PCA/PCoA plots, bar plots, box plots, heat maps, set intersection diagrams, bubble charts and volcano plots. A distinguishing feature of Visual Omics is that it allows users to perform one-stop omics data analyses without programming, iteratively explore the form and layout of graphs online and fine-tune parameters to generate charts that meet publication requirements.
Visual Omics can be used at http://bioinfo.ihb.ac.cn/visomics. Source code can be downloaded at http://bioinfo.ihb.ac.cn/software/visomics/visomics-1.1.tar.gz.
Supplementary data are available at Bioinformatics online.
随着高通量测序技术的不断发展，组学数据的生物信息分析在生命科学研究中发挥着越来越重要的作用。许多 R 包被广泛应用于组学分析，如 DESeq2、clusterProfiler 和 STRINGdb。并且，基于这些 R 包已经开发了一些在线工具，以将这些 R 包从编程中解放出来。然而，这些工具生成的图表通常是固定的、不可编辑的格式，并且经常无法清晰地展示研究人员想要表达的细节。为了解决这些问题，我们创建了 Visual Omics，这是一个用于组学数据分析和科学图表编辑的在线工具。Visual Omics 集成了多种组学分析，包括差异表达分析、富集分析、蛋白质结构域预测和蛋白质-蛋白质相互作用分析，具有广泛的图形展示。它还可以独立绘制和自定义涉及组学分析的基本图表，如各种 PCA/PCoA 图、柱状图、箱线图、热图、集合交集图、气泡图和火山图。Visual Omics 的一个显著特点是，它允许用户无需编程即可一站式进行组学数据分析，在线迭代探索图形的形式和布局，并微调参数以生成符合出版要求的图表。
Visual Omics 可在 http://bioinfo.ihb.ac.cn/visomics 使用。源代码可在 http://bioinfo.ihb.ac.cn/software/visomics/visomics-1.1.tar.gz 下载。
补充数据可在 Bioinformatics 在线获取。
