Unleashing genotypes in epidemiology - A novel method for managing high throughput information

Abstract

The large amounts of data generated when high-throughput genotyping methods are used in large-scale epidemiological studies (>10,000 participants) present an enormous challenge to researchers in terms of structured data management. In order to face these challenges, a system has been designed and implemented where genotype data can be efficiently stored. Focus has been on enabling researchers to collaborate by sharing genotype data with each other in a secure and controlled way. Genotype data is available where individuals can be selected using phenotype information and access to specific SNPs can be controlled using user-defined filters. Further value has been added to the basic genotypic information by including extensive metadata. Performance testing of the system was carried out using both artificial and real-world genotype data and shows that the implementation handles large datasets with a linear increase in extraction time and that the retrieval performance is more than sufficient for near-future genotyping research.