graphevne -传染病图形分析管道开发环境。

Q1 Medicine
Wellcome Open Research Pub Date : 2025-05-27 eCollection Date: 2025-01-01 DOI:10.12688/wellcomeopenres.23824.1
John-Stuart Brittain, Joseph Tsui, Rhys Inward, Bernardo Gutierrez, Gaspary Mwanyika, Houriiyah Tegally, Tuyen Huynh, George Githinji, Sofonias Kifle Tessema, John T McCrone, Samir Bhatt, Abhishek Dasgupta, Stephen Ratcliffe, Moritz U G Kraemer
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引用次数: 0

摘要

传染病及其驱动因素相关数据的数量和多样性的增加为产生新的科学见解提供了机会,这些见解可以支持在疫情背景下公共卫生领域的“实时”决策,并加强大流行防范。然而,由于数据预处理、数据科学能力以及对硬件和云资源的访问方面的差异,利用全球收集的广泛的临床、基因组、流行病学和空间数据是困难的。为了方便在地方一级对传染病数据进行大规模和常规分析(即不跨境共享数据),我们开发了GRAPEVNE(图形分析管道开发环境),这是一个平台,可以通过直观的图形界面构建模块化管道,用于复杂和重复的数据分析工作流程。基于Snakemake工作流管理系统,GRAPEVNE简化了分析管道的创建、执行和共享。其模块化方法已经支持多种科学应用,包括基因组分析、流行病学建模和大规模数据处理。GRAPEVNE中的每个模块都是一个自包含的Snakemake工作流,完成配置,脚本和元数据,实现互操作性。该平台的开源特性确保了持续的社区驱动开发和可扩展性。GRAPEVNE使研究人员和公共卫生机构能够简化复杂的分析工作流程,促进数据驱动的发现,并提高计算研究的可重复性。其用户驱动的生态系统鼓励生物医学和流行病学研究的持续创新,但适用于此之外。主要用例包括病毒序列的自动系统发育分析、实时爆发监测、预测和流行病学数据处理。例如,我们的登革热病毒管道展示了从序列检索到系统地理推断的端到端自动化,利用了可部署到任何地理环境的已建立的生物信息学工具。有关详细信息,请参阅文档:https://grapevne.readthedocs.io。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

GRAPEVNE - Graphical Analytical Pipeline Development Environment for Infectious Diseases.

GRAPEVNE - Graphical Analytical Pipeline Development Environment for Infectious Diseases.

GRAPEVNE - Graphical Analytical Pipeline Development Environment for Infectious Diseases.

The increase in volume and diversity of relevant data on infectious diseases and their drivers provides opportunities to generate new scientific insights that can support 'real-time' decision-making in public health across outbreak contexts and enhance pandemic preparedness. However, utilising the wide array of clinical, genomic, epidemiological, and spatial data collected globally is difficult due to differences in data preprocessing, data science capacity, and access to hardware and cloud resources. To facilitate large-scale and routine analyses of infectious disease data at the local level (i.e. without sharing data across borders), we developed GRAPEVNE (Graphical Analytical Pipeline Development Environment), a platform enabling the construction of modular pipelines designed for complex and repetitive data analysis workflows through an intuitive graphical interface. Built on the Snakemake workflow management system, GRAPEVNE streamlines the creation, execution, and sharing of analytical pipelines. Its modular approach already supports a diverse range of scientific applications, including genomic analysis, epidemiological modeling, and large-scale data processing. Each module in GRAPEVNE is a self-contained Snakemake workflow, complete with configurations, scripts, and metadata, enabling interoperability. The platform's open-source nature ensures ongoing community-driven development and scalability. GRAPEVNE empowers researchers and public health institutions by simplifying complex analytical workflows, fostering data-driven discovery, and enhancing reproducibility in computational research. Its user-driven ecosystem encourages continuous innovation in biomedical and epidemiological research but is applicable beyond that. Key use-cases include automated phylogenetic analysis of viral sequences, real-time outbreak monitoring, forecasting, and epidemiological data processing. For instance, our dengue virus pipeline demonstrates end-to-end automation from sequence retrieval to phylogeographic inference, leveraging established bioinformatics tools which can be deployed to any geographical context. For more details, see documentation at: https://grapevne.readthedocs.io.

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来源期刊
Wellcome Open Research
Wellcome Open Research Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)
CiteScore
5.50
自引率
0.00%
发文量
426
审稿时长
1 weeks
期刊介绍: Wellcome Open Research publishes scholarly articles reporting any basic scientific, translational and clinical research that has been funded (or co-funded) by Wellcome. Each publication must have at least one author who has been, or still is, a recipient of a Wellcome grant. Articles must be original (not duplications). All research, including clinical trials, systematic reviews, software tools, method articles, and many others, is welcome and will be published irrespective of the perceived level of interest or novelty; confirmatory and negative results, as well as null studies are all suitable. See the full list of article types here. All articles are published using a fully transparent, author-driven model: the authors are solely responsible for the content of their article. Invited peer review takes place openly after publication, and the authors play a crucial role in ensuring that the article is peer-reviewed by independent experts in a timely manner. Articles that pass peer review will be indexed in PubMed and elsewhere. Wellcome Open Research is an Open Research platform: all articles are published open access; the publishing and peer-review processes are fully transparent; and authors are asked to include detailed descriptions of methods and to provide full and easy access to source data underlying the results to improve reproducibility.
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