The Journal of Supercomputing

, Volume 72, Issue 12, pp 4696–4717 | Cite as

Performance comparison of sequential and parallel compression applications for DNA raw data

  • Aníbal GuerraEmail author
  • Jaime Lotero
  • Sebastián Isaza


We present an experimental performance comparison of lossless compression programs for DNA raw data in FASTQ format files. General-purpose (PBZIP2, P7ZIP and PIGZ) and domain-specific compressors (SCALCE, QUIP, FASTQZ and DSRC) were analyzed in terms of compression ratio, execution speed, parallel scalability and memory consumption. Results showed that domain-specific tools increased the compression ratios up to 70 %, while reducing the runtime of general-purpose tools up to \(7\times \) during compression and up to \(3\times \) during decompression. Parallelism scaled performance up to \(13\times \) when using 20 threads. Our analysis indicates that QUIP, DSRC and PBZIP2 are the best tools in their respective categories, with acceptable memory requirements. Nevertheless, the end user must consider the features of available hardware and define the priorities among its optimization objectives (compression ratio, runtime during compression or decompression, scalability, etc.) to properly select the best application for each particular scenario.


DNA raw data compression Performance evaluation Parallel scalability Memory consumption Bioinformatics 



We want to thank Felipe Cabarcas and Juan Fernando Alzate from the Centro Nacional de Secuenciación Genómica at the University of Antioquia for giving us access to their computing cluster and test data; and for their help in clarifying many bioinformatics related issues. This work was supported by the University of Antioquia under project code PRV15-2-02.


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Facultad de Ciencias y Tecnología FaCyTUniversidad de Carabobo UCValenciaVenezuela
  2. 2.Facultad de IngenieríaUniversidad de Antioquia UdeA, Calle 70 No. 52-21MedellínColombia

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