Road to FAIR genomes: a gap analysis of NGS data generation and sharing in the Netherlands

Q1 Medicine BMJ Open Science Pub Date : 2022-04-01 DOI:10.1136/bmjos-2021-100268
J. Belien, A. Kip, M. Swertz
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引用次数: 1

Abstract

Objective This study investigates current standards and operational gaps in the management and sharing of next generation sequencing (NGS) data within the healthcare and research setting and according to Findable, Accessible, Interoperable and Reusable (FAIR) principles. Methods The analysis was performed as the basis from which to bridge identified gaps and develop widely accepted working standards that ensure optimal reusability of genomic data in healthcare and research settings in the Netherlands. This work is part of the ‘Rational Pharmacotherapy Program’ led by ZonMw, The Netherlands Organisation for Health Research and Development, which aims to promote the efficient implementation of NGS and personalised medicine within Dutch healthcare, with an initial focus on oncology and rare diseases. Results Based on this analysis and as part of this programme, a consortium was formed to develop an instruction manual for FAIR genomic data in clinical care and research based on an inventory of commonly used workflows and standards in the (inter)national field of genome analysis. Conclusions The gap analysis presented and discussed in this paper represents the starting point for this inventory and is a possible contribution from the Netherlands to the European 1+ Million Genomes Initiative. This paper addresses the topics of data generation, data quality, (meta)data standards, data storage and archiving and data integration and exchange.
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通往公平基因组之路:荷兰NGS数据生成和共享的差距分析
目的本研究根据可查找、可访问、可互操作和可重复使用(FAIR)原则,调查医疗保健和研究环境中下一代测序(NGS)数据管理和共享的现行标准和操作差距。方法该分析是弥合已发现的差距并制定广泛接受的工作标准的基础,以确保基因组数据在荷兰医疗保健和研究环境中的最佳可重用性。这项工作是荷兰卫生研究与发展组织ZonMw领导的“合理药物治疗计划”的一部分,该计划旨在促进荷兰医疗保健中NGS和个性化药物的有效实施,最初重点关注肿瘤学和罕见病。结果基于这一分析,作为该计划的一部分,成立了一个联盟,根据国家间基因组分析领域常用的工作流程和标准清单,为临床护理和研究中的FAIR基因组数据制定指导手册。结论本文中提出和讨论的差距分析是该清单的起点,也是荷兰对欧洲100多万基因组计划的可能贡献。本文讨论了数据生成、数据质量、(元数据)标准、数据存储和归档以及数据集成和交换等主题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMJ Open Science
BMJ Open Science Medicine-General Medicine
CiteScore
10.00
自引率
0.00%
发文量
9
审稿时长
31 weeks
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