Genomic Data Container with Field-Specific Compression and Metadata
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Solution Overview
Problem
Current genomic data storage mechanisms face issues with interoperability, inefficient compression, and lack of metadata support for security, privacy, and reproducibility verification, leading to suboptimal performance and management of diverse genomic annotation data.
Innovation Solution
A unified data format and system that integrates functional metadata into a file structure for genomic data, including user profiles, analytics information, access history, and linkage information, which is compressed and stored in a container data structure, enabling secure, traceable, and reproducible data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If general compression algorithms are used for genomic annotation data, then compression is performed, but compression performance is suboptimal because the algorithms do not exploit the statistical characteristics of different fields
Solution Approach 1:
The patent segments genomic annotation data into multiple fields (e.g., chromosome, start position, end position, gene name, expression level) and applies different compression algorithms to each field based on its statistical characteristics. This allows optimal compression for each field type while maintaining overall system manageability.
Solution Approach 2:
The patent implements field-specific compression strategies where each field in the genomic annotation data receives compression treatment tailored to its properties. For example, numeric fields like coordinates use different compression than categorical fields like gene names, achieving local optimization that improves overall compression performance.
2Adaptability or versatility
If multiple different formats are used for diverse genomic annotation data, then data representation flexibility is maintained, but interoperability issues arise and frequent format conversions are needed
Solution Approach 1:
The patent creates a universal genomic annotation data format that can represent multiple types of genomic data (VCF, BED, GTF, GFF, Wig, BigWig, BedGraph, HiC) within a single standardized structure. This unified format eliminates the need for frequent format conversions while maintaining the ability to represent diverse data types through flexible field definitions.
3Reliability
If prior art storage mechanisms are used, then basic data storage is achieved, but functional metadata for advanced features such as data security, privacy, authenticity, and access tracking is lacking
Solution Approach 1:
The patent incorporates functional metadata (security credentials, privacy settings, authenticity verification data, access tracking information) directly into the data structure during the initial data creation and storage process. This preliminary inclusion of metadata eliminates the need for separate metadata management systems and ensures security and authenticity features are built-in from the start.
4Manufacturing precision
If diverse genomic annotation data types are stored in different formats, then each data type can be represented appropriately, but the need for frequent conversions between formats increases operational complexity
Solution Approach 1:
The patent implements a universal container format that can hold diverse genomic annotation data types (variants, gene expressions, functional annotations, quantitative tracks, chromosome conformation data) without requiring conversion. The format uses type indicators and field definitions to appropriately represent each data type while eliminating conversion time and operational complexity.
Data Source
AI summary
A method (100) for storing genomic data within a data structure comprising a file structure, comprising: (i) receiving (120) a genomic dataset comprising a plurality of fields or attributes of different data types; (ii) generating (130) an information metadata structure for the genomic dataset, comprising one or more of: information about an annotation table, including one or more user profiles and associated profile permission; analytics information configured to facilitate verification of data reproducibility; access history for the genomic dataset, configured to facilitate data traceability; and linkage information defining a relationship between the annotation table and one or more data objects; (ii) compressing (140) the genomic data and information metadata using a compression algorithm; and (iv) storing (150) the compressed genomic dataset and information metadata in a container data structure; wherein some or all of the annotation table is encrypted.