Abstract Title

The Great Lakes Atlas of Multi-omics Research (GLAMR) Database: Facilitating the Great Lakes Research of Tomorrow

Start Date

25-5-2022 9:30 AM

End Date

25-5-2022 9:45 AM

Abstract

Research and monitoring of harmful algal blooms increasingly relies on ‘Omics information obtained by characterizing and quantifying biomolecules including DNA, RNA, proteins, and metabolites. While individual studies and/or types of ‘omics data produce valuable insights on their own, additional insights can be gained by integrating the complex relationships of multi-omics data from multiple studies in a unified database with environmental data. With this in mind, we are building a database to facilitate analyses of ‘omics data collected from the Great Lakes, including analysis of complex interactions and across expanded time and geographic scales. While the database will support many types of queries, users will–for example–be able to compare across annual Cyanobacteria blooms, where toxin production and strain abundance vary considerably over time. Here we present the concept and architecture of this database, progress on loading existing datasets, use case scenarios, and example output. From the research community, we seek input on desired capabilities and use-cases, and additional high-quality Great Lakes datasets for inclusion in the database. By addressing common barriers to analysis of ‘omics data—including bioinformatics expertise and the need for high-performance computing—the database will expand public data access both for experts and inexperienced users.

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May 25th, 9:30 AM May 25th, 9:45 AM

The Great Lakes Atlas of Multi-omics Research (GLAMR) Database: Facilitating the Great Lakes Research of Tomorrow

Research and monitoring of harmful algal blooms increasingly relies on ‘Omics information obtained by characterizing and quantifying biomolecules including DNA, RNA, proteins, and metabolites. While individual studies and/or types of ‘omics data produce valuable insights on their own, additional insights can be gained by integrating the complex relationships of multi-omics data from multiple studies in a unified database with environmental data. With this in mind, we are building a database to facilitate analyses of ‘omics data collected from the Great Lakes, including analysis of complex interactions and across expanded time and geographic scales. While the database will support many types of queries, users will–for example–be able to compare across annual Cyanobacteria blooms, where toxin production and strain abundance vary considerably over time. Here we present the concept and architecture of this database, progress on loading existing datasets, use case scenarios, and example output. From the research community, we seek input on desired capabilities and use-cases, and additional high-quality Great Lakes datasets for inclusion in the database. By addressing common barriers to analysis of ‘omics data—including bioinformatics expertise and the need for high-performance computing—the database will expand public data access both for experts and inexperienced users.