Sequence Read Storage Using Unique-Read Compression
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Solution Overview
Problem
Current methods for storing and transferring sequencing data generated by next-generation sequencing technologies are inefficient due to the large volume of data, leading to high storage and transfer costs, and existing compression methods are unsatisfactory as they are lossy or not human-readable.
Innovation Solution
The method involves identifying and storing only unique sequence information from redundant sequence read files, using algorithms to compress data into human-readable text files, reducing storage needs and transfer costs while allowing for lossless retrieval of original data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sequencing data is stored in full redundancy to maintain 10x or 100x coverage, then data completeness and reliability are improved, but storage space requirements and transfer costs increase significantly
Solution Approach 1:
The patent extracts and stores only the unique sequence information from redundant sequencing reads, separating the essential unique data from the duplicative reads. This extraction principle reduces storage requirements while preserving all unique sequence information needed for complete genomic coverage analysis.
Solution Approach 2:
The patent discards duplicative sequence reads during storage, keeping only unique sequences. When data is needed, the unique sequences are recovered and can be virtually reconstructed into the original redundant format for analysis, maintaining reliability while minimizing storage space.
2Volume of stationary object
If existing compression methods are used to reduce file size, then storage space is reduced, but the compressed files become lossy or not human-readable
Solution Approach 1:
The patent creates a simplified copy of the sequencing data that stores only unique sequence information in a human-readable text format. This copy contains all essential information in a compressed form that is both space-efficient and fully interpretable, avoiding the information loss typical of conventional compression methods.
3Loss of information
If all sequence reads are stored in detail, then complete information is preserved, but data transfer bandwidth requirements and costs increase
Solution Approach 1:
The patent extracts only the essential unique sequence information from the complete set of reads, removing all duplicative data. This extraction enables efficient data transfer with reduced bandwidth requirements while preserving all unique sequence information needed for complete genomic analysis.
4Volume of stationary object
If conventional binary compression formats are used, then file size is reduced, but the files become inaccessible to general-purpose text editors and scripts
Solution Approach 1:
The patent uses a homogeneous text-based format for storing unique sequence information that is universally accessible to text editors, scripts, and analysis tools. This homogeneous text format maintains small file size while ensuring maximum compatibility and ease of operation across different software environments.
Data Source
AI summary
The present invention generally relates to storing sequence read data. The invention can involve obtaining a plurality of sequence reads from a sample, identifying one or more sets of duplicative sequence reads within the plurality of sequence reads, and storing only one of the sequence reads from each set of duplicative sequence reads in a text file using nucleotide characters.