An open-source, integrated pedigree data management and visualization tool for genetic epidemiology.

Area of Science:

• Biomedical Informatics
• Genetic Epidemiology
• Bioinformatics

Background:

• Biomedical data management systems often lack family-centric data models.
• Managing large family datasets, including twin studies, requires specialized approaches.
• Existing systems necessitate computing expertise for family-specific data extraction.

Purpose of the Study:

• To present a robust approach for handling large family datasets.
• To extend The Ark, an open-source biomedical data management tool, with family-centric capabilities.
• To facilitate dynamic inference and management of family relationships within biomedical studies.

Main Methods:

• Implementation of a new pedigree module extending The Ark.
• Development of an algorithm for dynamic inference of family relationships.
• Creation of a web interface for managing parental and twin relationships, including bulk import/export.
• Integration of consanguinity capture and configurable pedigree visualizations.
• Inclusion of a web services interface for interoperability.

Main Results:

• A robust system for handling large family datasets is now available.
• The pedigree module dynamically infers family relationships for any subject.
• Researchers can easily create, update, delete, and navigate family structures.
• Consanguineous relationships and detailed pedigree visualizations are supported.
• The system enhances interoperability through a web services interface.

Conclusions:

• The new module provides a powerful and flexible solution for managing complex family data in genetic epidemiology.
• This approach simplifies data management, reducing the need for specialized computing expertise.
• The enhanced The Ark tool supports comprehensive pedigree analysis and visualization, advancing family-centric research.