Reference Genome Reconstruction from Compressed Aligned Reads
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for compressing aligned genomic sequences lack efficiency when reference genomes are not available for decoding, leading to poor compression ratios and inability to reconstruct genomic data without the reference sequence.
Innovation Solution
A method for lossless compression of reference genomes using contig assembly, entropy coding of mismatch information, and selective reconstruction of reference sequences without requiring the original reference genome, employing Split Unit-wise Truncated Unary and Truncated Unary binarization techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If reference-based compression is used to achieve high compression ratios, then compression efficiency is improved, but the reference genome must be available at decoding which increases system complexity and storage requirements
Solution Approach 1:
The patent extracts only the essential information needed for decompression by encoding differences between the reference genome and assembled contig rather than storing the entire reference genome. This extraction approach achieves high compression ratios while eliminating the requirement to have the complete reference genome available at the decoding end.
Solution Approach 2:
Instead of copying and storing the entire reference genome, the patent creates a compressed representation by encoding only the differences (mismatches, insertions, deletions) between the reference and the assembled contig from sequencing reads. This copying strategy reduces storage requirements while maintaining the ability to reconstruct the reference genome when needed.
2Ease of operation
If general purpose compressors are used for reference-less compression, then ease of operation is improved, but compression ratios deteriorate to poor levels
Solution Approach 1:
The patent changes the fundamental parameter of how genomic data is represented by assembling contigs from sequencing reads and encoding the differences between these contigs and the reference genome. This parameter change enables achieving high compression ratios (better than general purpose compressors) while maintaining reference-less operation, thus improving both compression efficiency and operational simplicity.
3Reliability
If the reference genome is included in the compressed representation for storage, then reliability of reconstruction is improved, but compression efficiency deteriorates
Solution Approach 1:
The patent extracts only the differential information (mismatches, insertions, deletions) between the reference genome and the assembled contig for storage in the compressed representation. This extraction ensures that the reference genome can be reliably reconstructed by combining the stored differences with the contig, while maintaining high compression efficiency by avoiding storage of redundant reference genome data.
4Adaptability or versatility
If contig assembly is performed to enable reference-less compression, then adaptability is improved, but computational complexity increases
Solution Approach 1:
The patent segments the reference genome into contigs based on sequencing reads, which enables reference-less compression by allowing the system to work with smaller, manageable units. This segmentation approach provides adaptability for reference-less operation while reducing computational complexity compared to processing the entire reference genome at once, as the assembly and difference encoding can be performed on smaller contig segments.
Data Source
AI summary
The method and apparatus described in this disclosure include representing a reference genome in terms of syntax elements describing the differences between said reference genome and previously aligned genomic sequences. Each of the aligned genomic sequence is described by means of a subset of syntax elements. Syntax elements describing all the genomic sequences are partitioned in blocks according to their statistical properties. Each block of syntax elements is entropy coded. The entropy coded blocks are then concatenated to form a compressed bitstream. The differences between the reference genome and the aligned sequences are expressed in terms of syntax elements, which are embedded in the bitstream of coded blocks of syntax elements describing aligned reads. The disclosed method enables the reconstruction of the reference genome used for alignment when decoding the compressed genomic sequences while preserving different options of random access on the compressed data and enabling efficient compression.