The National Microbiome Data Collaborative: enabling microbiome science

Wood‐Charlson, Elisha M.; Anubhav,; Auberry, Deanna L.; Blanco, Hannah; Borkum, Mark; Corilo, Yuri; Davenport, Karen W.; Deshpande, Shweta; Devarakonda, Ranjeet; Drake, Meghan M.; Duncan, William D.; Flynn, Mark; Hays, D.; Hu, Bin; Huntemann, Marcel; Li, Po-E; Lipton, Mary; Lo, Chien‐Chi; Millard, David E.; Miller, Kayd; Piehowski, Paul; Purvine, Samuel O.; Reddy, T. B. K.; Shakya, Migun; Sundaramurthi, Jagadish Chandrabose; Vangay, Pajau; Wei, Yaxing; Wilson, Bruce E.; Canon, Shane; Chain, Patrick; Fagnan, Kjiersten; Martin, Stanton; McCue, Lee Ann; Mungall, Christopher J.; Mouncey, Nigel J.; Maxon, Mary E.; Eloe‐Fadrosh, Emiley A.

doi:10.1038/s41579-020-0377-0

Cited by 45 publications

(37 citation statements)

References 9 publications

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“…KEYWORDS data standards, metadata, microbiome, ontology T he National Microbiome Data Collaborative (NMDC) is a pilot initiative that was launched in July 2019 and is funded by the Department of Energy (DOE) Office of Science, Biological and Environmental Research Program, to support microbiome data exploration and discovery through a collaborative, integrative data science ecosystem (1). The NMDC team is building an open-source, integrated data science ecosystem that leverages existing data standards, data resources, and infrastructure in the microbiome research space.…”

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confidence: 99%

Microbiome Metadata Standards: Report of the National Microbiome Data Collaborative’s Workshop and Follow-On Activities

Vangay

Burgin²,

Johnston

et al. 2021

mSystems

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Microbiome samples are inherently defined by the environment in which they are found. Therefore, data that provide context and enable interpretation of measurements produced from biological samples, often referred to as metadata, are critical. Important contributions have been made in the development of community-driven metadata standards; however, these standards have not been uniformly embraced by the microbiome research community. To understand how these standards are being adopted, or the barriers to adoption, across research domains, institutions, and funding agencies, the National Microbiome Data Collaborative (NMDC) hosted a workshop in October 2019. This report provides a summary of discussions that took place throughout the workshop, as well as outcomes of the working groups initiated at the workshop.

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confidence: 99%

Microbiome Metadata Standards: Report of the National Microbiome Data Collaborative’s Workshop and Follow-On Activities

Vangay

Burgin²,

Johnston

et al. 2021

mSystems

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“…Such projects serve as an example of the type of work that could be better supported with quality improvements in metadata. The National Microbiome Collaborative is working with the community to specifically address data reuse including metadata quality (13,14).…”

Section: Development Of Machine Learning (Ml)mentioning

confidence: 99%

Current challenges in microbiome metadata collection

Rosenfeld

Angelova

Shin

et al. 2021

Preprint

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While the biomedical community has embraced data sharing (e.g. results, raw data) and supported establishment of large research consortia (e.g. the Human Microbiome Project) aimed to standardize the quality of important sets of microbiome sequencing data, the reusability of most microbiome data is still limited by the quality of its associated metadata. To ensure that microbiome data is indeed FAIR (Findable, Accessible, Interoperable, and Reusable), it is necessary to consider tools and approaches that make it easier to provide high-quality metadata that is fit for purpose moving forward. Such tools and approaches could be informed by current efforts to harmonize and improve the quality of extant microbiome metadata.

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“…Inconsistency and uncontrolled metadata filling were demonstrated by Gonçalves and Musen (46), revealing the necessity of standardized metadata compilation (47). (23,45) to promote data discovery and reuse in the microbiome field, and allow for broader dissemination of knowledge and compliance for both humans and machines.…”

Section: Introductionmentioning

confidence: 99%

SKIOME Project: a curated collection of skin microbiome datasets enriched with study-related metadata

Agostinetto¹,

Bozzi²,

Porro

et al. 2021

Preprint

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Large amounts of data from microbiome-related studies have been (and are currently being) deposited on international public databases. These datasets represent a valuable resource for the microbiome research community and could serve future researchers interested in integrating multiple datasets into powerful meta-analyses. However, this huge amount of data lacks harmonization and is far from being completely exploited in its full potential to build a foundation that places microbiome research at the nexus of many subdisciplines within and beyond biology. Thus, urges the need for data accessibility and reusability, according to FAIR (Findable, Accessible, Interoperable, and Reusable) principles, as supported by National Microbiome Data Collaborative and FAIR Microbiome. To tackle the challenge of accelerating discovery and advances in skin microbiome research, we collected, integrated and organized existing microbiome data resources from human skin 16S rRNA amplicon sequencing experiments. We generated a comprehensive collection of datasets, enriched in metadata, and organized this information into data frames ready to be integrated into microbiome research projects and advanced post-processing analysis, such as data science applications (e.g. machine learning). Furthermore, we have created a data retrieval and curation framework built on three different stages to maximize the retrieval of datasets and metadata associated with them. Lastly, we highlighted some caveats regarding metadata retrieval and suggested ways to improve future metadata submissions. Overall, our work resulted in a curated skin microbiome datasets collection accompanied by a state-of-the-art analysis of the last 10 years of the skin microbiome field.

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The National Microbiome Data Collaborative: enabling microbiome science

Cited by 45 publications

References 9 publications

Microbiome Metadata Standards: Report of the National Microbiome Data Collaborative’s Workshop and Follow-On Activities

Microbiome Metadata Standards: Report of the National Microbiome Data Collaborative’s Workshop and Follow-On Activities

Current challenges in microbiome metadata collection

SKIOME Project: a curated collection of skin microbiome datasets enriched with study-related metadata

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