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生物信息学基础设施的发展用于基因组学研究。

Development of Bioinformatics Infrastructure for Genomics Research.

机构信息

Computational Biology Division, Department of Integrative Biomedical Sciences, Institute for Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.

Department of Computer and Information Sciences, Covenant University, Ota, Nigeria; Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Nigeria.

出版信息

Glob Heart. 2017 Jun;12(2):91-98. doi: 10.1016/j.gheart.2017.01.005. Epub 2017 Mar 13.

Abstract

BACKGROUND

Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet's role has evolved in response to changing needs from the consortium and the African bioinformatics community.

OBJECTIVES

H3ABioNet set out to develop core bioinformatics infrastructure and capacity for genomics research in various aspects of data collection, transfer, storage, and analysis.

METHODS AND RESULTS

Various resources have been developed to address genomic data management and analysis needs of H3Africa researchers and other scientific communities on the continent. NetMap was developed and used to build an accurate picture of network performance within Africa and between Africa and the rest of the world, and Globus Online has been rolled out to facilitate data transfer. A participant recruitment database was developed to monitor participant enrollment, and data is being harmonized through the use of ontologies and controlled vocabularies. The standardized metadata will be integrated to provide a search facility for H3Africa data and biospecimens. Because H3Africa projects are generating large-scale genomic data, facilities for analysis and interpretation are critical. H3ABioNet is implementing several data analysis platforms that provide a large range of bioinformatics tools or workflows, such as Galaxy, the Job Management System, and eBiokits. A set of reproducible, portable, and cloud-scalable pipelines to support the multiple H3Africa data types are also being developed and dockerized to enable execution on multiple computing infrastructures. In addition, new tools have been developed for analysis of the uniquely divergent African data and for downstream interpretation of prioritized variants. To provide support for these and other bioinformatics queries, an online bioinformatics helpdesk backed by broad consortium expertise has been established. Further support is provided by means of various modes of bioinformatics training.

CONCLUSIONS

For the past 4 years, the development of infrastructure support and human capacity through H3ABioNet, have significantly contributed to the establishment of African scientific networks, data analysis facilities, and training programs. Here, we describe the infrastructure and how it has affected genomics and bioinformatics research in Africa.

摘要

背景

尽管在非洲已经出现了一些生物信息学方面的卓越中心,但总体而言,大规模基因组数据分析一直受到专业知识和基础设施的限制。H3ABioNet 是一个泛非生物信息学网络,其成立的目的是专门建立能力,使 H3Africa(非洲人类遗传与健康)的研究人员能够在非洲分析他们的数据。自 H3Africa 计划启动以来,H3ABioNet 的角色随着联盟和非洲生物信息学界不断变化的需求而发展。

目的

H3ABioNet 的目标是开发基因组学研究的核心生物信息学基础设施和能力,涵盖数据收集、传输、存储和分析的各个方面。

方法和结果

开发了各种资源来满足 H3Africa 研究人员和非洲大陆其他科学界的基因组数据管理和分析需求。开发了 NetMap 来构建非洲内部以及非洲与世界其他地区网络性能的准确图景,并推出了 Globus Online 来促进数据传输。开发了一个参与者招募数据库来监测参与者的登记情况,并通过使用本体和控制词汇来协调数据。标准化元数据将被整合,为 H3Africa 数据和生物样本提供搜索功能。由于 H3Africa 项目正在生成大规模的基因组数据,因此分析和解释的设施至关重要。H3ABioNet 正在实施几个数据分析平台,这些平台提供了广泛的生物信息学工具或工作流程,例如 Galaxy、作业管理系统和 eBiokits。还正在开发一组可重复、可移植且可在云环境中扩展的管道,以支持多种 H3Africa 数据类型,并将其 Docker 化,以便在多种计算基础设施上执行。此外,还开发了用于分析独特的非洲数据和下游解释优先级变体的新工具。为了支持这些和其他生物信息学查询,建立了一个由广泛的联盟专业知识支持的在线生物信息学帮助台。还通过各种生物信息学培训模式提供进一步的支持。

结论

在过去的 4 年中,通过 H3ABioNet 的基础设施支持和人力资源开发,极大地促进了非洲科学网络、数据分析设施和培训计划的建立。在这里,我们描述了基础设施以及它如何影响非洲的基因组学和生物信息学研究。

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