ABI Development: Open-source, extensible, and cross-platform MEGA

ABI 开发：开源、可扩展、跨平台 MEGA

• 批准号: 1661218
• 负责人: Sudhir Kumar
• 金额: $ 99.84万
• 依托单位: Temple University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1661218&HistoricalAwards=false
• 关键词: ABI; Development; Open; source; extensible

Comparative analyses of DNA and amino acid sequences is a powerful paradigm in biology, including evolution, ecology, development, and medicine. The Molecular Evolutionary Genetics Analysis (MEGA) software is a widely used tool to apply state-of-the-art methods for sequence analysis in these biological disciplines. MEGA provides an intuitive graphical user interface (GUI) to enable researchers to explore their primary data and results interactively, along with an integrated analytical engine that makes a large repertoire of evolutionary analysis methods easily accessible. MEGA is used by thousands of researchers in biology and has become a major teaching tool in universities worldwide. However, MEGA is primarily for use on Windows operating systems, which limits its utility and impact. The goal of this project is to (a) make MEGA cross-platform; (b) ready MEGA for community contributions and third-party expansion of functionalities; and (c) add a workflow GUI in MEGA to enable researchers to assemble pipelines and workflows that are becoming essential for rigorous, reproducible, and automated analytics in this era of big data. These developments will lead to a major enhancement of software infrastructure in biology and related interdisciplinary areas, all of which are critical in modern biological research. They will advance education through the development of tutorials, and benefit underserved populations through workshops and teaching. Comparative analyses of DNA and amino acid sequences, a powerful paradigm in computational biology, have grown and adapted to the changing needs of biological sciences. Due to its increasing analytical complexity, successful application of the comparative paradigm requires efficient, sophisticated, and intuitive software. The Molecular Evolutionary Genetics Analysis (MEGA, now in version 7) software is among the most widely used tools for sequence analysis, as it provides a powerful and intuitive graphical user interface (GUI), giving researchers tools for exploring their data and visualizing results interactively, and placing a large repertoire of state-of-the-art evolutionary analysis methods at their fingertips. This "Development" proposal is to modernize and re-engineer MEGA using cutting edge software libraries and development philosophies. It will ensure that this vital community resource not only remains useful for the next decade, but also becomes cross-platform and extensible for community integration of new methods and tools. The project will leverage modern open source application development stacks and libraries, drawing upon web technologies (JavaScript, HTML5, and CSS) for a platform agnostic application, which will lead to an open source, cross-platform MEGA GUI that is ready for community contributions and third-party expansion of functionalities. It will also add a new workflow system (AppFlows) to enable researchers to assemble pipelines and workflows that are becoming essential for rigorous, reproducible, and automated analytics in this era of big data. The new AppDepot in MEGA will host add-ins and extensions (small and large) developed by community programmers by reusing MEGA-X components and core libraries. AppDepot will bridge the gap between computational/statistical method developers and biological users, as the large installed base of MEGA will immediately make new methods available to many to test and use. All of these results will be available from www.megasoftware.net .

DNA和氨基酸序列的比较分析是生物学中的一个强有力的范例，包括进化，生态学，发展和医学。分子进化遗传学分析（MEGA）软件是一种广泛使用的工具，可将最先进的方法应用于这些生物学科的序列分析。MEGA提供了一个直观的图形用户界面（GUI），使研究人员能够交互式地探索他们的主要数据和结果，沿着一个集成的分析引擎，使大量的进化分析方法易于访问。MEGA被成千上万的生物学研究人员使用，并已成为世界各地大学的主要教学工具。然而，MEGA主要用于Windows操作系统，这限制了其实用性和影响力。该项目的目标是（a）使MEGA跨平台;（B）为社区贡献和第三方功能扩展做好准备;（c）在MEGA中添加工作流GUI，使研究人员能够组装管道和工作流，这些管道和工作流对于大数据时代的严格，可复制和自动化分析至关重要。这些发展将导致生物学和相关跨学科领域的软件基础设施的重大增强，所有这些都是现代生物学研究的关键。他们将通过编写教程促进教育，并通过讲习班和教学使得不到充分服务的人口受益。DNA和氨基酸序列的比较分析是计算生物学中一个强大的范例，已经发展并适应了生物科学不断变化的需求。由于其日益增加的分析复杂性，比较范式的成功应用需要高效，复杂和直观的软件。分子进化遗传学分析（MEGA，现在是第7版）软件是最广泛使用的序列分析工具之一，因为它提供了一个强大而直观的图形用户界面（GUI），为研究人员提供了交互式探索数据和可视化结果的工具，并将大量最先进的进化分析方法放在他们的指尖。这个“发展”的建议是现代化和重新设计的MEGA使用先进的软件库和开发理念。它将确保这一重要的社区资源不仅在未来十年内仍然有用，而且还可以跨平台扩展，以便社区集成新的方法和工具。该项目将利用现代开源应用程序开发堆栈和库，利用Web技术（JavaScript，HTML5和CSS）开发平台无关的应用程序，这将导致一个开源，跨平台的MEGA GUI，为社区贡献和第三方功能扩展做好准备。它还将添加一个新的工作流系统（AppFlows），使研究人员能够组装管道和工作流，这些管道和工作流对于大数据时代的严格，可重复和自动化分析至关重要。MEGA中的新AppDepot将托管社区程序员通过重用MEGA-X组件和核心库开发的加载项和扩展（小型和大型）。AppDepot将弥合计算/统计方法开发人员和生物用户之间的差距，因为MEGA的庞大安装基础将立即使许多人可以测试和使用新方法。所有这些结果都将在www.megasoftware.net上提供。

项目成果

Adventures in Evolution: The Narrative of Tardigrada, Trundlers in Time

进化历险记：缓步动物的叙述，时间中的拖车者

• DOI: 10.1525/abt.2019.81.8.543
• 发表时间: 2019
• 期刊: The American Biology Teacher
• 作者: Babaian, Caryn;Kumar, Sudhir
• 通讯作者: Kumar, Sudhir

Relative Efficiencies of Simple and Complex Substitution Models in Estimating Divergence Times in Phylogenomics

• DOI: 10.1093/molbev/msaa049
• 发表时间: 2020-02
• 期刊: Molecular Biology and Evolution
• 影响因子: 10.7
• 作者: Qiqing Tao;Jose Barba-Montoya;Louise A. Huuki;Mary Kathleen Durnan;Sudhir Kumar

Reliable Confidence Intervals for RelTime Estimates of Evolutionary Divergence Times

• DOI: 10.1093/molbev/msz236
• 发表时间: 2020-01-01
• 期刊: MOLECULAR BIOLOGY AND EVOLUTION
• 影响因子: 10.7
• 作者: Tao, Qiqing;Tamura, Koichiro;Kumar, Sudhir
• 通讯作者: Kumar, Sudhir

Molecular Evolutionary Genetics Analysis (MEGA) for macOS

• DOI: 10.1093/molbev/msz312
• 发表时间: 2020-04-01
• 期刊: MOLECULAR BIOLOGY AND EVOLUTION
• 影响因子: 10.7
• 作者: Stecher, Glen;Tamura, Koichiro;Kumar, Sudhir
• 通讯作者: Kumar, Sudhir

A new method for inferring timetrees from temporally sampled molecular sequences

• DOI: 10.1371/journal.pcbi.1007046
• 发表时间: 2020-01-01
• 期刊: PLOS COMPUTATIONAL BIOLOGY
• 影响因子: 4.3
• 作者: Miura, Sayaka;Tamura, Koichiro;Kumar, Sudhir
• 通讯作者: Kumar, Sudhir