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GeCo2: An Optimized Tool for Lossless Compression and Analysis of DNA Sequences

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Book cover Practical Applications of Computational Biology and Bioinformatics, 13th International Conference (PACBB 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1005 ))

Abstract

The development of efficient DNA data compression tools is fundamental for reducing the storage, given the increasing availability of DNA sequences. The importance is also reflected for analysis purposes, given the search for optimized and new tools for anthropological and biomedical applications. In this paper, we describe the characteristics and impact of the GeCo2 tool, an improved version of the GeCo tool. In the proposed tool, we enhanced the mixture of models, where each context model or tolerant context model has now a specific decay factor. Additionally, specific cache-hash sizes and the ability to run only a context model with inverted repeats was developed. A new command line interface, twelve new pre-computed levels, and several optimizations in the code were also included. The results show a compression improvement using less computational resources (RAM and processing time). This new version permits more flexibility for compression and analysis purposes, namely a higher ability of addressing different characteristics of the DNA sequences. The decompression is performed using symmetric computational resources (RAM and time). The GeCo2 is freely available, under GPLv3 license, at https://github.com/pratas/geco2.

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Acknowledgments

This work was partially funded by FEDER (Programa Operacional Factores de Competitividade - COMPETE) and by National Funds through the FCT, in the context of the projects UID/CEC/00127/2019 & PTCD/EEI-SII/6608/2014 and the grant PD/BD/113969/2015 to MH.

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Authors and Affiliations

  1. IEETA/DETI, University of Aveiro, Aveiro, Portugal

    Diogo Pratas, Morteza Hosseini & Armando J. Pinho

Authors
  1. Diogo Pratas
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  2. Morteza Hosseini
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  3. Armando J. Pinho
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Corresponding author

Correspondence to Armando J. Pinho .

Editor information

Editors and Affiliations

  1. Edificio Politécnico, Escuela Superior de Ingeniería Informática,Campus Universitario As Lagoas , Ourense, Spain

    Florentino Fdez-Riverola

  2. Department de Informática, Universidade do Minho, Braga, Portugal

    Miguel Rocha

  3. Faculty of Bioengineering and Technology, Universiti Malaysia Kelantan, Kelantan, Malaysia

    Mohd Saberi Mohamad

  4. Department of Computer Science and Software Engineering Leader, Data Science Research Group, College of Information Technology (CIT) United Arab Emirates University (UAEU), Al Ain, United Arab Emirates

    Nazar Zaki

  5. IBSAL/BISITE Research Group, University of Salamanca, Salamanca, Salamanca, Spain

    José A. Castellanos-Garzón

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Pratas, D., Hosseini, M., Pinho, A.J. (2020). GeCo2: An Optimized Tool for Lossless Compression and Analysis of DNA Sequences. In: Fdez-Riverola, F., Rocha, M., Mohamad, M., Zaki, N., Castellanos-Garzón, J. (eds) Practical Applications of Computational Biology and Bioinformatics, 13th International Conference. PACBB 2019. Advances in Intelligent Systems and Computing, vol 1005 . Springer, Cham. https://doi.org/10.1007/978-3-030-23873-5_17

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