| Literature DB >> 29659834 |
Thilina Ranaweera1, Enes Makalic1, John L Hopper1, Adrian Bickerstaffe1.
Abstract
With advances in genetic epidemiology, increasingly large amounts of pedigree-related information are being collected by family studies, including twin studies. To date, biomedical data management systems that cater for family data have usually done so as part of their standard (non-family-centric) data model. Consequently, data managers with computing expertise are needed to extract family datasets and perform family-centric operations. We present a robust approach to handling large family datasets. Our approach is implemented as a new module which extends the capabilities of The Ark, an open-source web-based biomedical data management tool. Using an algorithm designed by the authors, the pedigree module dynamically infers family relationships for any selected subject (not necessarily the proband). A web interface allows researchers to create, update, delete and navigate parental and twin relationships between subjects, and bulk import/export pedigrees. Consanguineous relationships can be captured, and configurable pedigree visualizations generated. A web services interface provides interoperability.Entities:
Mesh:
Year: 2018 PMID: 29659834 DOI: 10.1093/ije/dyy049
Source DB: PubMed Journal: Int J Epidemiol ISSN: 0300-5771 Impact factor: 7.196