Harmonization of GlyGen glycoconjugate and glycan array data for integration into CFDE - Glycans and glycoconjugates are critical to cellular communication, immunity, development, and disease processes, but remain underrepresented in biomedical data ecosystems. This project integrates GlyGen's glycoconjugate, glycan array, and protein variation data into the NIH Common Fund Data Ecosystem (CFDE), ensuring the unique data types are interoperable, findable, accessible, and reusable. The effort directly supports the CFDE mission to enable cross-domain biomedical research and advance precision medicine. The project introduces extensions to the data model for protein site-specific variation and glycan-protein datasets. The project will also prepare data in formats that support next-gen analytical methods, including machine learning and knowledge graph development, making the resources adaptable and broadly usable. The development of documentation, reusable workflows, and training materials will enhance reproducibility, interoperability, and community adoption. The GlyGen team will perform quarterly submissions of GlyGen metadata and datasets to the portal, with persistent access maintained through resolver services. Usage statistics and feedback will be collected to monitor adoption and guide improvements. Active engagement in steering committees, working groups, and public webinars will ensure alignment with consortium priorities. The project will participate in the Ontology Working Group and implement recommendations that will enable connecting GlyGen data with other DCC data and facilitate metadata submission. The team will provide expert suggestions on RFCs, contributing to consortium standards development. Education and training efforts will be coordinated with the Training Center to enhance workforce development and increase adoption of resources. Sustained mechanisms for access, usage monitoring, and outreach will be established. By integrating GlyGen data into CFDE, researchers will gain access to detailed maps connecting glycans, genes, proteins, and other -omics data. The integration will support unique glycan use cases, including exploring sequence variants in glyco-related genes, understanding glycan epitopes, and investigating glycosyltransferases in rare diseases. Collaboration with CFDE-DCCs will facilitate data exchange and tool sharing, enabling multi-disciplinary queries and hypothesis testing that were previously impossible, now possible through CFDE.
