A negative storage model for precise but compact storage of genetic variation data

Area of Science:

• Genomics
• Bioinformatics
• Data Storage

Background:

• Increasing genomic data necessitates efficient storage and retrieval solutions.
• Existing genomic data storage models (VOSM, FSM, BLSM) face trade-offs between precision, accuracy, and performance.
• Accurate genomic data interpretation requires precise state information for every base.

Purpose of the Study:

• To propose a novel genomic data storage model, the Negative Storage Model (NSM).
• To achieve both high precision and performance in genomic data storage and retrieval.
• To address the limitations of existing storage models in handling diverse sequencing data.

Main Methods:

• Developed the Negative Storage Model (NSM) encoding technique.
• Compared NSM performance and storage characteristics against Full Storage Model (FSM) and Block Storage Model (BLSM).
• Evaluated NSM's ability to store and retrieve precise genomic states from clinical and whole exome sequencing data.

Main Results:

• NSM significantly reduces storage requirements by storing only variant and missing base states.
• NSM demonstrates dramatic improvements in both storage efficiency and retrieval performance.
• The NSM approach maintains precision and accuracy across different sequencing data types.

Conclusions:

• The Negative Storage Model (NSM) offers a superior approach to genomic data storage.
• NSM effectively balances precision, accuracy, and performance, overcoming limitations of existing models.
• NSM facilitates more meaningful analysis and interpretation of the growing volume of genomic data.