Model, Integrate, Search... Repeat: A Sound Approach to Building Integrated Repositories of Genomic Data

Abstract

A wealth of public data repositories is available to drive genomics and clinical research. However, there is no agreement among the various data formats and models; in the common practice, data sources are accessed one by one, learning their specific descriptions with tedious efforts. In this context, the integration of genomic data and of their describing metadata becomes—at the same time—an important, difficult, and well-recognized challenge. In this chapter, after overviewing the most important human genomic data players, we propose a conceptual model of metadata and an extended architecture for integrating datasets, retrieved from a variety of data sources, based upon a structured transformation process; we then describe a user-friendly search system providing access to the resulting consolidated repository, enriched by a multi-ontology knowledge base. Inspired by our work on genomic data integration, during the COVID-19 pandemic outbreak we successfully re-applied the previously proposed model-build-search paradigm, building on the analogies among the human and viral genomics domains. The availability of conceptual models, related databases, and search systems for both humans and viruses will provide important opportunities for research, especially if virus data will be connected to its host, provider of genomic and phenotype information.