FASTR: Reimagining FASTQ via Compact Image-inspired Representation

TL;DR

FASTR introduces a lossless, compact, and efficient representation for FASTQ files that reduces size, accelerates compression/decompression, and enables direct downstream analysis, facilitating scalable and real-time genomics workflows.

Contribution

FASTR is a novel encoding scheme that combines nucleotides and quality scores into 8-bit values, improving compression, speed, and usability over traditional FASTQ formats.

Findings

Reduces file size by at least 2x compared to FASTQ.

Faster compression and decompression than existing tools.

Enables direct use of reads for downstream analysis without decompression.

Abstract

Motivation: High-throughput sequencing (HTS) enables population-scale genomics but generates massive datasets, creating bottlenecks in storage, transfer, and analysis. FASTQ, the standard format for over two decades, stores one byte per base and one byte per quality score, leading to inefficient I/O, high storage costs, and redundancy. Existing compression tools can mitigate some issues, but often introduce costly decompression or complex dependency issues. Results: We introduce FASTR, a lossless, computation-native successor to FASTQ that encodes each nucleotide together with its base quality score into a single 8-bit value. FASTR reduces file size by at least 2x while remaining fully reversible and directly usable for downstream analyses. Applying general-purpose compression tools on FASTR consistently yields higher compression ratios, 2.47, 3.64, and 4.8x faster compression, and 2.34, 1.96, 1.75x faster decompression than on FASTQ across Illumina, HiFi, and ONT reads. FASTR is machine-learning-ready, allowing reads to be consumed directly as numerical vectors or image-like representations. We provide a highly parallel software ecosystem for FASTQ-FASTR conversion and show that FASTR integrates with existing tools, such as minimap2, with minimal interface changes and no performance overhead. By eliminating decompression costs and reducing data movement, FASTR lays the foundation for scalable genomics analyses and real-time sequencing workflows. Availability and Implementation: https://github.com/ALSER-Lab/FASTR