The road towards data integration in human genomics: players, steps and interactions

Area of Science:

• Genomics and Bioinformatics
• Computational Biology
• Data Science

Background:

• Vast amounts of experimental genomic data are publicly available from global collaborations.
• Data heterogeneity in notations and formats hinders effective combination and analysis of these datasets.
• Data integration is a critical prerequisite for biological knowledge discovery from disparate sources.

Purpose of the Study:

• To describe a technological pipeline for genomic data production and integration.
• To propose a taxonomy for genomic data players involved in data management.
• To analyze challenges and computational environments for genomic data integration.

Main Methods:

• Development of a technological pipeline from data generation to integration.
• Creation of a taxonomy classifying genomic data stakeholders (contributors, hosts, consortia, integrators, consumers).
• Analysis of approximately 30 key players in genomic data management, focusing on integrators.

Main Results:

• A comprehensive pipeline for managing and integrating heterogeneous genomic data.
• A classification system (taxonomy) for understanding roles in genomic data management.
• Identification of key challenges in genomic data integration and evaluation of supporting computational environments.

Conclusions:

• Effective data integration builds multiple perspectives over genomic data, revealing insights not possible with incompatible formats.
• The proposed taxonomy aids in understanding the landscape of genomic data management.
• Addressing integration challenges and leveraging appropriate computational tools are vital for advancing genomic research.