Hughes Laura D, Lewis Scott A, Hughes Michael E
Division of Pulmonary and Critical Care Medicine, Washington University School of Medicine, St. Louis, Missouri, United States of America.
PLoS One. 2017 Nov 2;12(11):e0187457. doi: 10.1371/journal.pone.0187457. eCollection 2017.
RNA-sequencing (RNA-seq) and microarrays are methods for measuring gene expression across the entire transcriptome. Recent advances have made these techniques practical and affordable for essentially any laboratory with experience in molecular biology. A variety of computational methods have been developed to decrease the amount of bioinformatics expertise necessary to analyze these data. Nevertheless, many barriers persist which discourage new labs from using functional genomics approaches. Since high-quality gene expression studies have enduring value as resources to the entire research community, it is of particular importance that small labs have the capacity to share their analyzed datasets with the research community. Here we introduce ExpressionDB, an open source platform for visualizing RNA-seq and microarray data accommodating virtually any number of different samples. ExpressionDB is based on Shiny, a customizable web application which allows data sharing locally and online with customizable code written in R. ExpressionDB allows intuitive searches based on gene symbols, descriptions, or gene ontology terms, and it includes tools for dynamically filtering results based on expression level, fold change, and false-discovery rates. Built-in visualization tools include heatmaps, volcano plots, and principal component analysis, ensuring streamlined and consistent visualization to all users. All of the scripts for building an ExpressionDB with user-supplied data are freely available on GitHub, and the Creative Commons license allows fully open customization by end-users. We estimate that a demo database can be created in under one hour with minimal programming experience, and that a new database with user-supplied expression data can be completed and online in less than one day.
RNA测序(RNA-seq)和微阵列是用于测量整个转录组基因表达的方法。最近的进展使这些技术对于任何具有分子生物学经验的实验室来说都切实可行且成本可控。已经开发出了各种计算方法,以减少分析这些数据所需的生物信息学专业知识量。然而,仍然存在许多障碍,阻碍新实验室使用功能基因组学方法。由于高质量的基因表达研究作为整个研究界的资源具有持久价值,因此小型实验室有能力与研究界共享其分析后的数据集尤为重要。在这里,我们介绍ExpressionDB,这是一个用于可视化RNA-seq和微阵列数据的开源平台,几乎可以容纳任意数量的不同样本。ExpressionDB基于Shiny,这是一个可定制的Web应用程序,允许通过用R编写的可定制代码在本地和在线共享数据。ExpressionDB允许基于基因符号、描述或基因本体术语进行直观搜索,并且它包括用于根据表达水平、倍数变化和错误发现率动态过滤结果的工具。内置的可视化工具包括热图、火山图和主成分分析,确保为所有用户提供简化且一致的可视化。用于使用用户提供的数据构建ExpressionDB的所有脚本均可在GitHub上免费获得,并遵循知识共享许可协议,允许最终用户进行完全开放的定制。我们估计,只需最少的编程经验,不到一小时就能创建一个演示数据库,而使用用户提供的表达数据创建一个新数据库并上线不到一天即可完成。