Integrating human genome database into electronic health record with sequence alignment and compression mechanism

Area of Science:

• Genomics
• Bioinformatics
• Health Informatics

Background:

• The post-genomic era necessitates efficient management of vast human genome sequence data.
• Understanding the functional roles of genomic sequences remains a significant challenge.
• The rapid expansion of sequence information highlights critical needs for data compilation and storage solutions.

Purpose of the Study:

• To design and implement a "Human Genome Database System" for efficient storage and management of experimental sequence data.
• To integrate sequence alignment and data compression functionalities for enhanced data handling.
• To facilitate the analysis of relationships between diseases and genes by combining genomic data with electronic health records.

Main Methods:

• Development of a "Human Genome Database System" at National Taiwan University Hospital (NTUH).
• Integration of the NCBI alignment program (blastall) for automated sequence alignment and genomic positioning.
• Implementation of sequence difference encoding for effective data compression, achieving a compression ratio of 12.28.
• Incorporation of diverse query methods (specimen number, GI, sequence position) for rapid data retrieval.
• Integration with the NTUH Health Information System (HIS) electronic health record (EHR).

Main Results:

• Successful implementation of a user-friendly system for doctors to store and manage experimental sequence data.
• Achieved a data compression ratio of 12.28, significantly reducing storage space requirements.
• Enabled automated sequence alignment and identification of genomic positions.
• Provided versatile query functionalities for efficient data access.
• Facilitated the potential to explore correlations between genetic information and diseases.

Conclusions:

• The developed "Human Genome Database System" effectively addresses the challenges of managing large-scale genomic data.
• Integration of alignment, compression, and EHR data supports advanced genetic research and clinical applications.
• The system lays the groundwork for establishing a personalized genetic healthcare environment.