ARTÍCULO

SPRING: a next-generation compressor for FASTQ data

Autores: Chandak, S.; Tatwawadi, K.; Ochoa Álvarez, Idoia; Hernáez Arrazola, Mikel; Weissman, T.
Título de la revista: BIOINFORMATICS
ISSN: 1367-4803
Volumen: 35
Número: 15
Páginas: 2674 - 2676
Fecha de publicación: 2019
Resumen:
Motivation High-Throughput Sequencing technologies produce huge amounts of data in the form of short genomic reads, associated quality values and read identifiers. Because of the significant structure present in these FASTQ datasets, general-purpose compressors are unable to completely exploit much of the inherent redundancy. Although there has been a lot of work on designing FASTQ compressors, most of them lack in support of one or more crucial properties, such as support for variable length reads, scalability to high coverage datasets, pairing-preserving compression and lossless compression. Results In this work, we propose SPRING, a reference-free compressor for FASTQ files. SPRING supports a wide variety of compression modes and features, including lossless compression, pairing-preserving compression, lossy compression of quality values, long read compression and random access. SPRING achieves substantially better compression than existing tools, for example, SPRING compresses 195 GB of 25× whole genome human FASTQ from Illumina¿s NovaSeq sequencer to less than 7 GB, around 1.6× smaller than previous state-of-the-art FASTQ compressors. SPRING achieves this improvement while using comparable computational resources.