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  Facilitating accessible, rapid, and appropriate processing of ancient metagenomic data with AMDirT

Borry, M., Forsythe, A., Valtueña, A. A., Hübner, A., Ibrahim, A., Quagliariello, A., et al. (2023). Facilitating accessible, rapid, and appropriate processing of ancient metagenomic data with AMDirT. F1000Research, 12: 926. doi:10.12688/f1000research.134798.1.

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(last seen: Aug. 2023)
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 Urheber:
Borry, Maxime, Autor
Forsythe, Adrian, Autor
Valtueña, Aida Andrades, Autor
Hübner, Alexander, Autor
Ibrahim, Anan, Autor
Quagliariello, Andrea, Autor
White, Anna E., Autor
Kocher, Arthur1, Autor           
Vågene, Åshild J., Autor
Bartholdy, Bjørn Peare, Autor
Spurīte, Diāna, Autor
Ponce-Soto, Gabriel Yaxal, Autor
Neumann, Gunnar, Autor
Huang, I-Ting, Autor
Light, Ian, Autor
Velsko, Irina M., Autor
Jackson, Iseult, Autor
Frangenberg, Jasmin, Autor
Serrano, Javier G., Autor
Fumey, Julien, Autor
mehr..
Affiliations:
1Transmission, Infection, Diversification & Evolution Group (tide), Max Planck Institute of Geoanthropology, Max Planck Society, ou_3508663              

Inhalt

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Schlagwörter: metagenomics,environmental,palaeogenomics,aDNA,microbiome,metadata,microbial,FAIR data
 Zusammenfassung: Background: Access to sample-level metadata is important when selecting public metagenomic sequencing datasets for reuse in new biological analyses. The Standards, Precautions, and Advances in Ancient Metagenomics community (SPAAM, https://spaam-community.github.io) has previously published AncientMetagenomeDir, a collection of curated and standardised sample metadata tables for metagenomic and microbial genome datasets generated from ancient samples. However, while sample-level information is useful for identifying relevant samples for inclusion in new projects, Next Generation Sequencing (NGS) library construction and sequencing metadata are also essential for appropriately reprocessing ancient metagenomic data. Currently, recovering information for downloading and preparing such data is difficult when laboratory and bioinformatic metadata is heterogeneously recorded in prose-based publications.

Methods: Through a series of community-based hackathon events, AncientMetagenomeDir was updated to provide standardised library-level metadata of existing and new ancient metagenomic samples. In tandem, the companion tool 'AMDirT' was developed to facilitate automated metadata curation and data validation, as well as rapid data filtering and downloading.

Results: AncientMetagenomeDir was extended to include standardised metadata of over 5000 ancient metagenomic libraries. The companion tool 'AMDirT' provides both graphical- and command-line interface based access to such metadata for users from a wide range of computational backgrounds. We also report on errors with metadata reporting that appear to commonly occur during data upload and provide suggestions on how to improve the quality of data sharing by the community.

Conclusions: Together, both standardised metadata and tooling will help towards easier incorporation and reuse of public ancient metagenomic datasets into future analyses.

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Sprache(n): eng - English
 Datum: 2023-08-02
 Publikationsstatus: Online veröffentlicht
 Seiten: 15
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: Introduction
Methods
- Implementation
- Operation
Use cases
Discussion
- Results of library level metadata aggregation
- Common issues in ancient metagenomic library metadata
- Note on AMDirT generated pipeline scripts
- Future development
Data availability
- Source data
- Software availability
 Art der Begutachtung: Keine Begutachtung
 Identifikatoren: DOI: 10.12688/f1000research.134798.1
Anderer: gea0089
 Art des Abschluß: -

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Projektinformation

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Projektname : DAIRYCULTURES
Grant ID : 804884
Förderprogramm : Horizon 2020 (H2020)
Förderorganisation : European Commission (EC)
Projektname : PALEoRIDER
Grant ID : 771234
Förderprogramm : Horizon 2020 (H2020)
Förderorganisation : European Commission (EC)

Quelle 1

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Titel: F1000Research
Genre der Quelle: Webseite
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Seiten: - Band / Heft: 12 Artikelnummer: 926 Start- / Endseite: - Identifikator: URN: https://f1000research.com/