Jointly Integrating VCF-Based Variants and OWL-Based Biomedical Ontologies in MongoDB

Area of Science:

• Genomics
• Bioinformatics
• Database Management

Background:

• Next-generation sequencing (NGS) generates vast amounts of Variant Call Format (VCF) data.
• Web Ontology Language (OWL) is widely used for biomedical ontologies, leading to large-scale ontology growth.
• Current data management struggles with the scale and interchange of VCF and OWL data.

Purpose of the Study:

• To develop an effective method for managing VCF-based genetic variants and OWL-based biological ontologies.
• To leverage MongoDB for storing and querying integrated biomedical data.
• To address the need for efficient data handling in genomics and ontology research.

Main Methods:

• Proposed rules for mapping VCF and OWL files to JSON (JavaScript Object Notation).
• Developed rule-based algorithms to transform VCF and OWL data into JSON objects.
• Implemented approaches for integrating mapped JSON files into MongoDB.
• Conducted experiments to evaluate the performance of the proposed methods.

Main Results:

• Successfully mapped VCF and OWL data to JSON format.
• Demonstrated effective integration of JSON-formatted genetic variants and ontologies in MongoDB.
• Experimental results validated the performance of the proposed data management and integration approaches.
• Source code is available for public use.

Conclusions:

• The proposed method provides an effective solution for managing and integrating large-scale VCF and OWL data using MongoDB.
• The JSON-based transformation facilitates data interchange and future expansion.
• This approach supports the growing needs of biomedical research in genomics and ontology management.