通过标准化数据和元数据收集推进微生物组研究:介绍微生物组研究数据工具包。

IF 3.4 4区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Lyndon Zass, Lamech M Mwapagha, Adetola F Louis-Jacques, Imane Allali, Julius Mulindwa, Anmol Kiran, Mariem Hanachi, Oussama Souiai, Nicola Mulder, Ovokeraye H Oduaran
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引用次数: 0

摘要

随着测序技术的发展,微生物组研究取得了重大成果。确保研究之间的可比性,提高微生物组数据的可查找性、可访问性、互操作性和可重复性,对于最大限度地发挥这一不断增长的研究成果的价值至关重要。为了应对标准化元数据报告、收集和整理方面的挑战,非洲人类遗传与健康(H3Africa)联盟微生物组工作组旨在开发一种全面的解决方案。在本文中,我们介绍了微生物组研究数据工具包,这是一个多功能工具,旨在实现微生物组研究元数据的标准化、促进 MIxS-MIMS 和 PhenX 报告、实现参与者生物和生活方式数据前瞻性收集的标准化,并对此类数据进行回顾性协调。该工具包使过去、现在和未来的微生物组研究工作能够有效合作,促进新的合作并加速该领域的知识发现。数据库网址:https://doi.org/10.25375/uct.24218999.v2。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advancing microbiome research through standardized data and metadata collection: introducing the Microbiome Research Data Toolkit.

Microbiome research has made significant gains with the evolution of sequencing technologies. Ensuring comparability between studies and enhancing the findability, accessibility, interoperability and reproducibility of microbiome data are crucial for maximizing the value of this growing body of research. Addressing the challenges of standardized metadata reporting, collection and curation, the Microbiome Working Group of the Human Hereditary and Health in Africa (H3Africa) consortium aimed to develop a comprehensive solution. In this paper, we present the Microbiome Research Data Toolkit, a versatile tool designed to standardize microbiome research metadata, facilitate MIxS-MIMS and PhenX reporting, standardize prospective collection of participant biological and lifestyle data, and retrospectively harmonize such data. This toolkit enables past, present and future microbiome research endeavors to collaborate effectively, fostering novel collaborations and accelerating knowledge discovery in the field. Database URL: https://doi.org/10.25375/uct.24218999.v2.

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来源期刊
Database: The Journal of Biological Databases and Curation
Database: The Journal of Biological Databases and Curation MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
9.00
自引率
3.40%
发文量
100
审稿时长
>12 weeks
期刊介绍: Huge volumes of primary data are archived in numerous open-access databases, and with new generation technologies becoming more common in laboratories, large datasets will become even more prevalent. The archiving, curation, analysis and interpretation of all of these data are a challenge. Database development and biocuration are at the forefront of the endeavor to make sense of this mounting deluge of data. Database: The Journal of Biological Databases and Curation provides an open access platform for the presentation of novel ideas in database research and biocuration, and aims to help strengthen the bridge between database developers, curators, and users.
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