Key Lab of Organic-based Fertilizers of China and Jiangsu Provincial Key Lab for Solid Organic Waste Utilization, Nanjing Agricultural University, Nanjing, 210095, China.
China Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, China; Key Laboratory of Multiomics Research and Clinical Transformation of Digestive Cancer, China.
Comput Biol Med. 2024 Mar;171:108206. doi: 10.1016/j.compbiomed.2024.108206. Epub 2024 Feb 28.
The rapid growth of omics technologies has led to the use of bioinformatics as a powerful tool for unravelling scientific puzzles. However, the obstacles of bioinformatics are compounded by the complexity of data processing and the distinct nature of omics data types, particularly in terms of visualization and statistics.
We developed a comprehensive and free platform, CFViSA, to facilitate effortless visualization and statistical analysis of omics data by the scientific community.
CFViSA was constructed using the Scala programming language and utilizes the AKKA toolkit for the web server and MySQL for the database server. The visualization and statistical analysis were performed with the R program.
CFViSA integrates two omics data analysis pipelines (microbiome and transcriptome analysis) and an extensive array of 79 analysis tools spanning simple sequence processing, visualization, and statistics available for various omics data, including microbiome and transcriptome data. CFViSA starts from an analysis interface, paralleling a demonstration full course to help users understand operating principles and scientifically set the analysis parameters. Once analysis is conducted, users can enter the task history interface for figure adjustments, and then a complete series of results, including statistics, feature tables and figures. All the graphic layouts were printed with necessary statistics and a traceback function recording the options for analysis and visualization; these statistics were excluded from the five competing methods.
CFViSA is a user-friendly bioinformatics cloud platform with detailed guidelines for integrating functions in multi-omics analysis with real-time visualization adjustment and complete series of results provision. CFViSA is available at http://www.cloud.biomicroclass.com/en/CFViSA/.
组学技术的快速发展使得生物信息学成为解决科学难题的有力工具。然而，生物信息学的障碍因数据处理的复杂性和组学数据类型的独特性质而变得更加复杂，特别是在可视化和统计学方面。
我们开发了一个全面且免费的平台 CFViSA，以方便科学界轻松地对组学数据进行可视化和统计分析。
CFViSA 是使用 Scala 编程语言构建的，并使用 AKKA 工具包作为 Web 服务器，MySQL 作为数据库服务器。可视化和统计分析是使用 R 程序进行的。
CFViSA 集成了两个组学数据分析管道（微生物组和转录组分析）以及广泛的 79 种分析工具，涵盖了各种组学数据（包括微生物组和转录组数据）的简单序列处理、可视化和统计分析。CFViSA 从分析接口开始，模拟了一个完整的演示课程，以帮助用户理解操作原理并科学地设置分析参数。一旦进行了分析，用户可以进入任务历史界面进行图形调整，然后得到一系列完整的结果，包括统计信息、特征表和图形。所有图形布局都打印了必要的统计信息和一个回溯功能，记录了分析和可视化的选项；这些统计信息不包括五个竞争方法。
CFViSA 是一个用户友好的生物信息学云平台，具有详细的指导方针，用于整合多组学分析中的功能，具有实时可视化调整和完整系列结果的提供。CFViSA 可在 http://www.cloud.biomicroclass.com/en/CFViSA/ 上获得。
