Publicação
Design and implementation of a database-driven software for genetic variant interpretation
| Resumo: | As genomic data volumes continue to grow, managing and integrating this information for clinically meaningful interpretation becomes increasingly complex. These challenges are particularly evident during tertiary analysis, where insights depend on combining multiple and heterogeneous data sources. Although there are commercial software solutions developed to streamline this process, they impose rigid data models and restricted export capabilities that limit interoperability, leaving institutions dependent on proprietary ecosystems and risking the loss of valuable interpretation records as platforms change. To address this, the internship project focused on developing a custom solution to preserve institutional knowledge. The work involved designing a structured database, implementing a reliable ETL pipeline, and creating a user-friendly web application that enables efficient search, filtering, and review of variant interpretation data. The resulting system establishes an extensible workflow adaptable to future data formats, sources, and tools, enhancing both accessibility and clinical utility. |
|---|---|
| Autores principais: | Pinheiro, Inês Morgado |
| Assunto: | Clinical bioinformatics Genomic data integration Tertiary analysis Relational database Web application |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Aveiro |
| Idioma: | inglês |
| Origem: | RIA - Repositório Institucional da Universidade de Aveiro |
| Resumo: | As genomic data volumes continue to grow, managing and integrating this information for clinically meaningful interpretation becomes increasingly complex. These challenges are particularly evident during tertiary analysis, where insights depend on combining multiple and heterogeneous data sources. Although there are commercial software solutions developed to streamline this process, they impose rigid data models and restricted export capabilities that limit interoperability, leaving institutions dependent on proprietary ecosystems and risking the loss of valuable interpretation records as platforms change. To address this, the internship project focused on developing a custom solution to preserve institutional knowledge. The work involved designing a structured database, implementing a reliable ETL pipeline, and creating a user-friendly web application that enables efficient search, filtering, and review of variant interpretation data. The resulting system establishes an extensible workflow adaptable to future data formats, sources, and tools, enhancing both accessibility and clinical utility. |
|---|