Literature DB >> 19616640

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

George Olund1, Anders Brinne, Pontus Lindqvist, Jan-Eric Litton.   

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.

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Year:  2009        PMID: 19616640     DOI: 10.1016/j.jbi.2009.07.005

Source DB:  PubMed          Journal:  J Biomed Inform        ISSN: 1532-0464            Impact factor:   6.317


  1 in total

1.  Damming the genomic data flood using a comprehensive analysis and storage data structure.

Authors:  Marc Bouffard; Michael S Phillips; Andrew M K Brown; Sharon Marsh; Jean-Claude Tardif; Tibor van Rooij
Journal:  Database (Oxford)       Date:  2010-12-15       Impact factor: 3.451

  1 in total

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