HyPhy: comprehensive, fast, and user-friendly software for evolutionary analysis

 描述(由申请人提供)：hyphy(：//www.hyphy.org)是一个可编写脚本的软件平台，设计用于在进化环境中对DNA、RNA、密码子、氨基酸和其他类型的序列数据进行灵活和强大的分析。自从2005年首次正式发布以来，Hyphy和它的免费Web服务器Data Monkey(：//www.datamonkey.org)已经变得稳定和成熟，在2000多种同行评议的出版物中被引用，在多本书的章节中进行了描述，并成为许多受邀研讨会的主题。在第一个四年的资金周期中，我们把重点放在改善和强化Hyphy系统的“后端”元素上。在本提案中，虽然我们仍将在这一级别进行工作，但我们更多地将重点放在“前端”上 与用户的互动是关键。目标1：重新设计HYPHY分析引擎及其脚本语言1.1重新设计HYPHY批处理语言(HBL)，以增强其生产率、可靠性、可维护性、可移植性和可重用性；这将在保持向后兼容性的同时完成。1.2重新开发进化模型、标准分析和推理程序的标准库，使其具有自我文档化、易于学习、易于扩展、对意外错误应用的健壮性，并符合数据交换格式和通信协议。目标2：大型和复杂数据集的模型和算法。2.1通过加速硬件和软件中的基本操作，提高hyphy性能，以便在单个分析中处理更大的数据集。2.2允许用户将序列和其他量化数据组合在似然框架中。2.3建立一个快速进化的病原体和免疫谱系的分析资料库。目标3：用于所有计算设备的基于Web浏览器的图形界面。目前，大多数HYPHY用户通过www.datamonkey.org与该计划互动。考虑到对这种用户体验的需求，我们将：3.1作为本地Web应用程序实现用于数据探索、分析定义、作业执行以及结果解释和可视化的完整接口。该界面将在计算机、桌面和智能手机上运行。3.2将hyphy的计算核心开发为本地浏览器插件，使hyphy成为完全在浏览器中分发、维护和运行的“应用程序”。3.3使用现代网络技术(node.js)重新实施datamonkey.org；提供可从任何hyphy实例访问的公共实例，以及允许实验室建立自己的基于群集或云的实例的分发。

 DESCRIPTION (provided by applicant): HyPhy (://www.hyphy.org) is a scriptable software platform designed to enable flexible and powerful analyses of DNA, RNA, codon, amino acid and other types of sequence data in an evolutionary context. Since their initial formal release in 2005, HyPhy and it's free web server Data Monkey (://www.datamonkey.org) have become stable and mature, cited in over 2,000 peer-reviewed publications, described in multiple book chapters, and been the subject of many invited workshops. In the first four-year funding cycle we focused on improvements and hardening of the "back end" elements of the HyPhy system. In this proposal, while we will still do work at that level, we focus more on the "front end" where interactions with users are key. Aim 1: Re-architect the HyPhy analytical engine and its scripting language 1.1 Redesign the HyPhy Batch Language (HBL) to enhance its productivity, reliability, maintain- ability, portability and reusability; this will be done while maintaining backward compatibility. 1.2 Redevelop the standard library of evolutionary models, standard analyses, and inference procedures to make them self-documenting, easy to learn, easy to extend, robust to inadvertent misapplication, and compliant with data exchange formats and communication protocols. Aim 2: Models and algorithms for large and complex datasets. 2.1 Improve HyPhy performance to handle much larger data sets in a single analysis by accelerating the fundamental operations in hardware and software. 2.2 Allow users to combine sequence and other quantitative data in a likelihood framework. 2.3 Develop a library of analyses for rapidly evolving pathogens and immune repertoires. Aim 3: Web browser based graphical interface for all computing devices. Presently, the majority of HyPhy users interact with the program through www.datamonkey.org. Keeping in mind the demand for such a user experience, we will: 3.1 Implement a complete interface for data exploration, analysis definition, job execution, and result interpretation and visualization as a local web application. This interface will run on computers, tables, and smartphones. 3.2 Develop the computational core of HyPhy as a native browser plug-in, making HyPhy an "app" distributed, maintained, and run entirely in a browser. 3.3 Re-implement datamonkey.org using modern web technologies (node.js); provide a public instance which can be accessed from any instance of HyPhy, and a distribution that can allow labs to set up their own cluster- or cloud-based instances.