Centre de coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), UMR INTERTRYP, F-34398 Montpellier, France.
South Green Bioinformatics Platform, Bioversity, CIRAD, Institut National de la Recherche Agronomique (INRA), IRD, Montpellier, France.
Gigascience. 2019 May 1;8(5). doi: 10.1093/gigascience/giz051.
The study of genetic variations is the basis of many research domains in biology. From genome structure to population dynamics, many applications involve the use of genetic variants. The advent of next-generation sequencing technologies led to such a flood of data that the daily work of scientists is often more focused on data management than data analysis. This mass of genotyping data poses several computational challenges in terms of storage, search, sharing, analysis, and visualization. While existing tools try to solve these challenges, few of them offer a comprehensive and scalable solution.
Gigwa v2 is an easy-to-use, species-agnostic web application for managing and exploring high-density genotyping data. It can handle multiple databases and may be installed on a local computer or deployed as an online data portal. It supports various standard import and export formats, provides advanced filtering options, and offers means to visualize density charts or push selected data into various stand-alone or online tools. It implements 2 standard RESTful application programming interfaces, GA4GH, which is health-oriented, and BrAPI, which is breeding-oriented, thus offering wide possibilities of interaction with third-party applications. The project home page provides a list of live instances allowing users to test the system on public data (or reasonably sized user-provided data).
This new version of Gigwa provides a more intuitive and more powerful way to explore large amounts of genotyping data by offering a scalable solution to search for genotype patterns, functional annotations, or more complex filtering. Furthermore, its user-friendliness and interoperability make it widely accessible to the life science community.
遗传变异的研究是生物学许多研究领域的基础。从基因组结构到种群动态,许多应用都涉及到遗传变异的使用。下一代测序技术的出现导致了如此多的数据涌入,以至于科学家们的日常工作往往更多地集中在数据管理上,而不是数据分析上。这种大量的基因分型数据在存储、搜索、共享、分析和可视化方面都带来了一些计算上的挑战。虽然现有的工具试图解决这些挑战,但很少有工具提供全面的、可扩展的解决方案。
Gigwa v2 是一个易于使用的、与物种无关的网络应用程序,用于管理和探索高密度基因分型数据。它可以处理多个数据库,可以安装在本地计算机上,也可以部署为在线数据门户。它支持各种标准的导入和导出格式,提供高级过滤选项,并提供可视化密度图或将选定数据推送到各种独立或在线工具的方法。它实现了 2 个标准的 RESTful 应用程序编程接口,GA4GH,以健康为导向,以及 BrAPI,以育种为导向,从而提供了与第三方应用程序广泛交互的可能性。项目主页提供了一个实时实例列表,允许用户在公共数据(或用户提供的合理大小的数据)上测试系统。
这个新版本的 Gigwa 通过提供一种可扩展的解决方案来搜索基因型模式、功能注释或更复杂的过滤,为探索大量基因分型数据提供了一种更直观、更强大的方式。此外,它的用户友好性和互操作性使其广泛适用于生命科学界。