Hecate: A Modular Genomic Compressor

TL;DR

Hecate is a modular, high-performance genomic compressor that outperforms existing tools in speed and compression ratio by employing a flexible, conditional coding architecture tailored for FASTA/FASTQ data streams.

Contribution

Hecate introduces a novel modular framework with multiple codecs and conditional coding strategies, achieving superior speed and compression efficiency for genomic data.

Findings

Outperforms state-of-the-art tools in speed and compression ratio

Provides exact random-access slicing and referential mode

Achieves 2 to 10 times faster compression at similar ratios

Abstract

We present Hecate, a modular lossless genomic compression framework. It is designed around uncommon but practical source-coding choices. Unlike many single-method compressors, Hecate treats compression as a conditional coding problem over coupled FASTA/FASTQ streams (control, headers, nucleotides, case, quality, extras). It uses per-stream codecs under a shared indexed block container. Codecs include alphabet-aware packing with an explicit side channel for out-of-alphabet residues, an auxiliary-index Burrows-Wheeler pipeline with custom arithmetic coding, and a blockwise Markov mixture coder with explicit model-competition signaling. This architecture yields high throughput, exact random-access slicing, and referential mode through streamwise binary differencing. In a comprehensive benchmark suite, Hecate provides the best compression vs. speed trade-offs against state-of-the-art established tools (MFCompress, NAF, bzip3, AGC), with notably stronger behaviour on large genomes and high-similarity referential settings. For the same compression ratio, Hecate is 2 to 10 times faster. When given the same time budget as other algorithms, Hecate achieves up to 5% to 10% better compression.