ACO:lossless quality score compression based on adaptive coding order.

Area of Science:

• Genomics
• Bioinformatics
• Data Compression

Background:

• High-throughput sequencing generates vast amounts of genome data, driving the need for efficient data compression.
• While DNA base compression has advanced, quality score compression remains a significant challenge in the DNA sequencing industry.
• The exponential growth of genomic data necessitates improved methods for managing and storing sequencing information.

Purpose of the Study:

• To address the challenge of compressing DNA quality scores in next-generation sequencing (NGS) data.
• To develop a novel, lossless compression method for quality scores that leverages inherent correlations within sequencing data.
• To improve the efficiency of DNA data compression for large-scale genome projects.

Main Methods:

• Proposed a novel lossless quality score compressor named Adaptive Coding Order (ACO).
• Developed ACO to adaptively traverse quality scores along the most correlative trajectory based on the sequencing process.
• Integrated adaptive arithmetic coding and an improved in-context strategy within the ACO framework.

Main Results:

• Achieved state-of-the-art quality score compression performance for next-generation sequencing (NGS) data.
• Demonstrated that ACO offers significant improvements in quality score compression with moderate computational complexity.
• Validated the effectiveness of ACO in compressing quality scores, outperforming existing methods.

Conclusions:

• ACO is a competent tool for quality score compression in bioinformatics.
• The Adaptive Coding Order (ACO) method has been adopted by the AVS (Audio Video coding Standard Workgroup of China).
• The ACO compressor is freely available, promoting its use and further development in the field.