Database Commons

a catalog of worldwide biological databases

Variant interpretation guidelines guide the process of determining the role of DNA variants in patients' health. Currently, hundreds of guidelines exist, each applicable to a particular clinical domain. However, they are scattered across multiple resources and scientific literature. To address this issue, we present VarGuideAtlas, a comprehensive repository of variant interpretation guidelines that compiles information from ClinGen, ClinVar, and PubMed. Our repository offers a user-friendly web interface with advanced search capabilities, enabling clinicians and researchers to efficiently find relevant guidelines tailored to specific genes, diseases, or variant types. We employ ontologies to characterize each guideline, ensuring consistency and improving interoperability with bioinformatics tools. VarGuideAtlas represents a significant advance toward standardizing variant interpretation practices, facilitating more informed decision-making, improved clinical outcomes, and more precise genomic research. VarGuideAtlas is publicly accessible via a web-based platform (https://genomics-hub.pros.dsic.upv.es:3016/).

Mutational hotspots are DNA regions with an abnormally high frequency of genetic variants. Identifying whether a variant is located in a mutational hotspot is critical for determining the variant's role in disorder predisposition, development, and treatment response. Despite their significance, current databases on mutational hotspots are limited to the oncology domain. However, identifying mutational hotspots is critical for any disorder in which genetics plays a role. This is true for the world's leading cause of death: cardiac disorders. In this work, we present CardioHotspots, a literature-based database of manually curated hotspots for cardiac diseases. This is the only database we know of that provides high-quality and easily accessible information about hotspots associated with cardiac disorders. CardioHotspots is publicly accessible via a web-based platform (https://genomics-hub.pros.dsic.upv.es:3099/). Database URL: https://genomics-hub.pros.dsic.upv.es:3099/.

BACKGROUND: Familiar cardiopathies are genetic disorders that affect the heart. Cardiologists face a significant problem when treating patients suffering from these disorders: most DNA variations are novel (i.e., they have not been classified before). To facilitate the analysis of novel variations, we present CardioGraph, a platform specially designed to support the analysis of novel variations and help determine whether they are relevant for diagnosis. To do this, CardioGraph identifies and annotates the consequence of variations and provides contextual information regarding which heart structures, pathways, and biological processes are potentially affected by those variations.
METHODS: We conducted our work through three steps. First, we define a data model to support the representation of the heterogeneous information. Second, we instantiate this data model to integrate and represent all the genomics knowledge available for familiar cardiopathies. In this step, we consider genomic data sources and the scientific literature. Third, the design and implementation of the CardioGraph platform. A three-tier structure was used: the database, the backend, and the frontend.
RESULTS: Three main results were obtained: the data model, the knowledge base generated with the instantiation of the data model, and the platform itself. The platform code has been included as supplemental material in this manuscript. Besides, an instance is publicly available in the following link: https://genomics-hub.pros.dsic.upv.es:3090 .
CONCLUSION: CardioGraph is a platform that supports the analysis of novel variations. Future work will expand the body of knowledge about familiar cardiopathies and include new information about hotspots, functional studies, and previously reported variations.