Abstract：
BACKGROUND: 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.
OBJECTIVE: We developed a comprehensive and free platform, CFViSA, to facilitate effortless visualization and statistical analysis of omics data by the scientific community.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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/.
OBJECTIVE: We developed a comprehensive and free platform, CFViSA, to facilitate effortless visualization and statistical analysis of omics data by the scientific community.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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/.
摘要：
背景：组学技术的快速发展导致了将生物信息学用作解开科学难题的强大工具。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加剧，特别是在可视化和统计方面。
目标：我们开发了一个全面的免费平台，CFViSA,促进科学界毫不费力地对组学数据进行可视化和统计分析。
方法：CFViSA是使用Scala编程语言构建的，并使用AKKA工具包作为Web服务器和MySQL作为数据库服务器。使用R程序进行可视化和统计分析。
结果：CFViSA集成了两个组学数据分析管道（微生物组和转录组分析）和一系列广泛的79种分析工具，涵盖了简单的序列处理。可视化,以及可用于各种组学数据的统计数据，包括微生物组和转录组数据。CFViSA从分析接口开始，并行演示完整课程，以帮助用户了解操作原理并科学设置分析参数。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,然后是一系列完整的结果，包括统计数据，功能表和图形。所有图形布局均打印有必要的统计数据和回溯功能，记录了分析和可视化的选项；这些统计数据被排除在五种竞争方法之外。
结论：CFViSA是一个用户友好的生物信息学云平台，具有详细的指南，用于集成多组分析中的功能，并具有实时可视化调整和完整系列结果提供。CFViSA可在http://www上获得。云。biomicroclass.com/en/CFViSA/.
目标：我们开发了一个全面的免费平台，CFViSA,促进科学界毫不费力地对组学数据进行可视化和统计分析。
方法：CFViSA是使用Scala编程语言构建的，并使用AKKA工具包作为Web服务器和MySQL作为数据库服务器。使用R程序进行可视化和统计分析。
结果：CFViSA集成了两个组学数据分析管道（微生物组和转录组分析）和一系列广泛的79种分析工具，涵盖了简单的序列处理。可视化,以及可用于各种组学数据的统计数据，包括微生物组和转录组数据。CFViSA从分析接口开始，并行演示完整课程，以帮助用户了解操作原理并科学设置分析参数。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,然后是一系列完整的结果，包括统计数据，功能表和图形。所有图形布局均打印有必要的统计数据和回溯功能，记录了分析和可视化的选项；这些统计数据被排除在五种竞争方法之外。
结论：CFViSA是一个用户友好的生物信息学云平台，具有详细的指南，用于集成多组分析中的功能，并具有实时可视化调整和完整系列结果提供。CFViSA可在http://www上获得。云。biomicroclass.com/en/CFViSA/.
