memRGC

memRGC compresses genome sequences by incorporating mutation-containing matches (MCMs) into reference-based encoding to reduce coding costs caused by mutations.

Key Features:

• Maximal Match Utilization: A maximal match is a contiguous, non-extendable subsequence common between two genomes, and mutations that break these matches increase compression coding costs.
• Mutation-Containing Matches (MCMs): Incorporates MCMs by allowing mutations within maximal matches so that longer match segments can be encoded, reducing coding cost and improving compression efficiency.
• Coprime Double-Window K-Mer Sampling: Employs a coprime double-window k-mer sampling search scheme to detect maximal matches and to extend matches across mismatches and neighboring maximal matches to form long MCMs.
• Performance Enhancement: Demonstrates an average compression improvement of 27% versus traditional reference-based genome compression methods and up to 50% improvement in some cases relative to state-of-the-art methods.
• Resource Efficiency: Optimized to reduce memory and decompression resource usage while maintaining comparable compression speed.

Scientific Applications:

• Genomic Data Compression: Enables more efficient reference-based compression of large genomic datasets by mitigating the impact of mutation-induced match fragmentation.
• Data Storage and Transmission: Reduces storage footprint and bandwidth requirements for archival and transmission of large-scale genome sequence collections.

Methodology:

Uses coprime double-window k-mer sampling to detect maximal matches, extends matches to include mismatches and neighboring maximal matches to form MCMs, and incorporates MCMs into the encoding to reduce coding costs.