Department of Environmental Immunology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany.
Perinatal Research Group, Saxonian Incubator for Clinical Translation (SIKT), Medical Faculty, Leipzig University, Leipzig, Germany.
BMC Bioinformatics. 2022 Jul 23;23(1):292. doi: 10.1186/s12859-022-04836-2.
With the widespread availability of microarray technology for epigenetic research, methods for calling differentially methylated probes or differentially methylated regions have become effective tools to analyze this type of data. Furthermore, visualization is usually employed for quality check of results and for further insights. Expert knowledge is required to leverage capabilities of these methods. To overcome this limitation and make visualization in epigenetic research available to the public, we designed EpiVisR.
The EpiVisR tool allows to select and visualize combinations of traits (i.e., concentrations of chemical compounds) and differentially methylated probes/regions. It supports various modes of enriched presentation to get the most knowledge out of existing data: (1) enriched Manhattan plot and enriched volcano plot for selection of probes, (2) trait-methylation plot for visualization of selected trait values against methylation values, (3) methylation profile plot for visualization of a selected range of probes against selected trait values as well as, (4) correlation profile plot for selection and visualization of further probes that are correlated to the selected probe. EpiVisR additionally allows exporting selected data to external tools for tasks such as network analysis.
The key advantage of EpiVisR is the annotation of data in the enriched plots (and tied tables) as well as linking to external data sources for further integrated data analysis. Using the EpiVisR approach will allow users to integrate data from traits with epigenetic analyses that are connected by belonging to the same individuals. Merging data from various data sources among the same cohort and visualizing them will enable users to gain more insights from existing data.
随着微阵列技术在表观遗传学研究中的广泛应用,用于调用差异甲基化探针或差异甲基化区域的方法已成为分析此类数据的有效工具。此外,可视化通常用于检查结果的质量并获得进一步的见解。需要专业知识来利用这些方法的功能。为了克服这一限制,并使表观遗传学研究中的可视化面向公众,我们设计了 EpiVisR。
EpiVisR 工具允许选择和可视化特征(即化合物浓度)和差异甲基化探针/区域的组合。它支持各种丰富呈现模式,以从现有数据中获取最多的知识:(1)富集曼哈顿图和富集火山图用于探针选择,(2)特征-甲基化图用于可视化选定特征值与甲基化值,(3)甲基化图谱用于可视化选定探针范围内的选定特征值,以及(4)相关图谱用于选择和可视化与选定探针相关的进一步探针。EpiVisR 还允许将选定的数据导出到外部工具,以执行网络分析等任务。
EpiVisR 的主要优势在于丰富的图(和相关表格)中的数据注释,以及与外部数据源的链接,以进行进一步的集成数据分析。使用 EpiVisR 方法将允许用户将来自与同一个体相关的特征的与表观遗传学分析相关的数据进行集成。合并同一队列中来自不同数据源的数据并对其进行可视化,将使用户能够从现有数据中获得更多见解。