Genomic Quality Value Encoding With Codebook Quantization

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Solution Overview

Problem

High-throughput sequencing technologies generate vast amounts of genomic data, leading to significant IT costs due to storage and transmission requirements, necessitating efficient compression methods for quality values associated with nucleotide sequences.

Innovation Solution

A method for encoding and decoding quality values in genomic data structures involves quantizing quality values using codebooks, reducing information density by mapping multiple quality values to a smaller quantized quality value alphabet, and using entropy encoders for further compression, while maintaining the integrity of sequencing data.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If quality values are stored with full precision, then data accuracy is maintained, but storage size and transmission costs increase significantly

Engineering Contradiction:
Improvequality value accuracyVSAvoidstorage size
Core Design Contradiction:
Measurement precisionVSQuantity of substance

Solution Approach 1:

The patent transforms quality values from their original high-precision format into a compressed representation by changing the parameter encoding. Quality values are mapped to a smaller alphabet of representative values, and the mapping relationships are encoded efficiently. This parameter transformation maintains the essential information needed for accuracy while dramatically reducing the storage requirements and transmission bandwidth needed.

Inventive Principle:
Principle #35Parameter changes

Solution Approach 2:

The patent creates a compressed copy of the quality value data through multiple encoding passes. Instead of storing raw quality values directly, it generates encoded representations that capture the essential information in a more compact form. The decoding process reconstructs the quality values from these compressed copies, maintaining accuracy while reducing storage size.

Inventive Principle:
Principle #26Copying

2Quantity of substance

If compression is applied to quality values, then storage and transmission costs are reduced, but data integrity and accuracy may be compromised

Engineering Contradiction:
Improvestorage sizeVSAvoiddata integrity
Core Design Contradiction:
Quantity of substanceVSReliability

Solution Approach 1:

The patent performs preliminary encoding actions on the quality values before final storage or transmission. Multiple encoding passes are applied in advance, transforming the data into a compressed format that preserves essential information. The decoding process then reverses these transformations, ensuring that the reconstructed quality values maintain their integrity and accuracy despite the compression.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent incorporates feedback mechanisms in the encoding and decoding process. The encoding transforms quality values through multiple passes, and the decoding reverses these transformations while maintaining fidelity. The system ensures that the compressed representation contains sufficient information to reconstruct the original quality values with acceptable accuracy, providing feedback on the quality of compression and reconstruction.

Inventive Principle:
Principle #23Feedback

3Productivity

If multiple encoding passes are used, then compression rate is improved, but processing time and computational complexity increase

Engineering Contradiction:
Improvecompression rateVSAvoidprocessing time
Core Design Contradiction:
ProductivityVSLoss of time

Solution Approach 1:

The patent segments the encoding process into multiple distinct passes, each performing a specific transformation on the quality values. The first pass performs initial encoding, the second pass refines the compression, and subsequent passes further optimize the representation. This segmentation allows for systematic compression while making the computational process more manageable and efficient.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent employs dynamic encoding strategies where the encoding parameters and transformations are adapted based on the characteristics of the input data. The multiple passes allow the system to dynamically adjust the level of compression and transformation applied at each stage, optimizing the balance between compression rate and processing efficiency based on the specific properties of the quality value data being encoded.

Inventive Principle:
Principle #15Dynamics

Data Source

PatentEP3652862B1Method for encoding and decoding of quality values of a data structure
Publication Date: 2022.05.11 GOTTFRIED WILHELM LEIBNIZ UNIV HANNOVER
  • EP3652862B1 patent drawingFigure 1
  • EP3652862B1 patent drawingFigure 2
  • EP3652862B1 patent drawing

AI summary

Method for encoding of quality values of a data structure, whereby said data structure comprises a set of genomic reads, wherein the method comprises the following steps executable by a data processing system: - ascertain the quality values of each read covering a certain index locus, - determine a codebook identifier identifying a specific codebook from a plurality of codebooks for said certain index locus based on the ascertained quality values of said certain index locus, whereby each code-book provides a mapping from a quality value of said quality value alphabet to a corresponding quantized quality value of a quantized quality value alphabet, - quantizing all ascertained quality values at said certain index locus using the specific codebook identified by the codebook identifier at said certain index locus in order to obtain for each quality value at said certain index locus a corresponding quantized quality value, and - encode all determined codebook identifiers using a first entropy encoder and encode all quantized quality values using a second entropy encoder or a set of encoders.