Data

Browser for Allele and Gene Expression and Localisation (BAGEL): An R Shiny App for OzCrop Genome-to-Phenome Workflows

Commonwealth Scientific and Industrial Research Organisation
Stevens, Lauren ; Ord, Louise ; Hyles, Jessica ; Suchecki, Rad ; Rathjen, Tina ; Dillon, Shannon ; McNeil, Meredith ; Andrew, Sam ; Fradgley, Nick ; Marquardt, Annelie
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=http://hdl.handle.net/102.100.100/712927?index=1&rft.title=Browser for Allele and Gene Expression and Localisation (BAGEL): An R Shiny App for OzCrop Genome-to-Phenome Workflows&rft.identifier=http://hdl.handle.net/102.100.100/712927?index=1&rft.publisher=Commonwealth Scientific and Industrial Research Organisation&rft.description=BAGEL R Shiny App is an online interface allowing researchers to visualise and interact with pre-computed genomics data and apply their domain expertise to filter long lists of candidate genes and Single Nucleotide Polymorphisms (SNPs). Currently, the tool uses OzWheat pre-computed SNP and transcriptome datasets to display SNP information including position, predicted amino acid changes and summary data. The user can also explore selected transcripts via a link to the Wheat Expression Browser and download sequence information to be used for the design of SNP-based markers. With these data visualisations and export functions, BAGEL supports the identification of candidate genes and provides user-friendly access to relevant data which underpins the OzWheat Genome-to-Phenome platform.Lineage: Genomic data and marker-trait associations as described by Hyles, J., et al. (2024). OzWheat; a genome-to-phenome platform to resolve complex traits for wheat pre-breeding and research and Dillon, S. et al. (2024). Integrated genome and transcriptome wide analysis uncovers gene regulatory networks and predicts flowering time in wheat.&rft.creator=Stevens, Lauren &rft.creator=Ord, Louise &rft.creator=Hyles, Jessica &rft.creator=Suchecki, Rad &rft.creator=Rathjen, Tina &rft.creator=Dillon, Shannon &rft.creator=McNeil, Meredith &rft.creator=Andrew, Sam &rft.creator=Fradgley, Nick &rft.creator=Marquardt, Annelie &rft.date=2025&rft.edition=v2&rft.relation=https://www.biorxiv.org/content/10.1101/2024.08.11.603522v1&rft_rights=Creative Commons Attribution 4.0 International Licence https://creativecommons.org/licenses/by/4.0/&rft_rights=Data is accessible online and may be reused in accordance with licence conditions&rft_rights=All Rights (including copyright) CSIRO 2025.&rft_subject=RShiny&rft_subject=OzWheat&rft_subject=OzBarley&rft_subject=OzCanola&rft_subject=OzOat&rft_subject=OzCrops&rft_subject=SNP&rft_subject=Data visualisation and computational (incl. parametric and generative) design&rft_subject=Design&rft_subject=BUILT ENVIRONMENT AND DESIGN&rft.type=dataset&rft.language=English Access the data
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Creative Commons Attribution 4.0 International Licence
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Data is accessible online and may be reused in accordance with licence conditions

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BAGEL R Shiny App is an online interface allowing researchers to visualise and interact with pre-computed genomics data and apply their domain expertise to filter long lists of candidate genes and Single Nucleotide Polymorphisms (SNPs). Currently, the tool uses OzWheat pre-computed SNP and transcriptome datasets to display SNP information including position, predicted amino acid changes and summary data. The user can also explore selected transcripts via a link to the Wheat Expression Browser and download sequence information to be used for the design of SNP-based markers. With these data visualisations and export functions, BAGEL supports the identification of candidate genes and provides user-friendly access to relevant data which underpins the OzWheat Genome-to-Phenome platform.
Lineage: Genomic data and marker-trait associations as described by Hyles, J., et al. (2024). OzWheat; a genome-to-phenome platform to resolve complex traits for wheat pre-breeding and research and Dillon, S. et al. (2024). Integrated genome and transcriptome wide analysis uncovers gene regulatory networks and predicts flowering time in wheat.

Available: 2025-10-27

Data time period: 2022-02-01 to 2032-02-01

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Related Publications

  • Associated with OzWheat: a genome-to-phenome platform to resolve complex traits for wheat pre-breeding and research\nJessica E. Hyles, Howard A. Eagles, Kerrie Ramm, Bjorg Sherman, Andrew Gock, Sandra Stops, Tanya Phongkham, Emmett Leyne, Tina Rathjen, Radoslaw Suchecki, Lauren Stevens, Louise Ord, Nick S. Fradgley, Meredith D. McNeil, Annelie Marquardt, Samuel C. Andrew, Kerrie Forrest, Russell F. Eastwood, Adam Norman, Annette Tredrea, Richard Trethowan, Ben Trevaskis, Shannon K. Dillon\nbioRxiv 2024.08.11.603522; doi: https://doi.org/10.1101/2024.08.11.603522
    url : www.biorxiv.org/content/10.1101/2024.08.11.603522v1

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Subjects
Built Environment and Design | Data Visualisation and Computational (Incl. Parametric and Generative) Design | Design | OzBarley | OzCanola | OzCrops | OzOat | OzWheat | RShiny | SNP |

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Identifiers
ACN 633 798 857