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SPRING: a next-generation compressor for FASTQ data.
Chandak, Shubham; Tatwawadi, Kedar; Ochoa, Idoia; Hernaez, Mikel; Weissman, Tsachy.
Afiliación
  • Chandak S; Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
  • Tatwawadi K; Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
  • Ochoa I; Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
  • Hernaez M; Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
  • Weissman T; Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
Bioinformatics ; 35(15): 2674-2676, 2019 08 01.
Article en En | MEDLINE | ID: mdl-30535063
ABSTRACT
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. AVAILABILITY AND IMPLEMENTATION SPRING can be downloaded from https//github.com/shubhamchandak94/SPRING. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Compresión de Datos / Secuenciación de Nucleótidos de Alto Rendimiento Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Compresión de Datos / Secuenciación de Nucleótidos de Alto Rendimiento Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos