Reference DNA Dictionary Compression for Large Genome Databases
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The vast size of genetic information databases, such as the 1000 Genomes project, makes it difficult for scientists to access and manage the wealth of genetic data, with current systems struggling to efficiently compress and store the large amounts of data, leading to limited retrieval capabilities and cumbersome updates.
Innovation Solution
A method involving the use of a predefined codeword dictionary constructed from reference DNA data to compress and store DNA data, allowing for efficient encoding, storage, and retrieval of genetic information by selecting the best-matching dictionary based on similarity thresholds and updating the dictionary dynamically for improved compression ratios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If genetic information databases store complete genomic sequences of many persons, then the database contains comprehensive genetic variation data, but the database size becomes vast (exceeding 200 Terabytes) making retrieval and management difficult
Solution Approach 1:
The patent extracts only the essential genetic variation information from complete genomic sequences by identifying and storing single nucleotide polymorphisms (SNPs) and other variants at specific positions. Instead of storing entire genomes, the system extracts and stores only the variable positions across multiple samples, dramatically reducing database size while preserving all genetic variation data needed for research.
Solution Approach 2:
The patent segments the genetic data by dividing complete genomic sequences into discrete variant positions. Each position in the database represents a specific genomic location with its observed variants across different samples. This segmentation transforms the data structure from continuous sequences to discrete, manageable units that can be efficiently stored and queried.
2Reliability
If scientists sequence genomes multiple times to ensure accuracy, then the genetic data becomes more reliable, but the data volume increases significantly
Solution Approach 1:
The patent merges information from multiple sequencing runs by consolidating observations at each genomic position. Instead of storing separate sequence data from each sequencing attempt, the system combines all observations and records the set of unique variants observed at each position, achieving comprehensive coverage while minimizing redundant storage.
3Adaptability or versatility
If the genetic information database is updated regularly with new sequencing data, then the database remains current and useful, but the updates become hard to manage due to the vast size
Solution Approach 1:
The patent establishes a predefined schema for genetic data storage before updates occur. The database structure is designed in advance to accommodate various types of genetic variants at specified positions, with predetermined data formats and storage conventions. This preliminary structuring enables straightforward integration of new sequencing data without requiring complex reorganization or management procedures during updates.
Data Source
AI summary
A method for compressing information by a computerized system, the method may include receiving a mixture of DNA data and additional information; and compressing the DNA data to provide compressed DNA data, wherein the compressing comprises encoding the DNA data by using a predefined codeword dictionary that was constructed based upon reference DNA data.