Unleashing genotypes in epidemiology - A novel method for managing high throughput information.
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.
Olund
George
G
Karolinska Institutet, Stockholm, Sweden.
Brinne
Anders
A
Lindqvist
Pontus
P
Litton
Jan-Eric
JE
D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D003628:Database Management Systems; D030541:Databases, Genetic; D005838:Genotype; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D008962:Models, Theoretical; D017720:Molecular Epidemiology / Q000379:methods*; D020641:Polymorphism, Single Nucleotide