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baseLess: lightweight detection of sequences in raw MinION data

bioRxiv (Cold Spring Harbor Laboratory)

Abstract

A bstract With its candybar form factor and low initial investment cost, the MinION brought affordable portable nucleic acid analysis within reach. However, translating the electrical signal it outputs into a sequence of bases still requires high-end computer hardware, which remains a caveat when aiming for deployment of many devices at once or usage in remote areas. For applications focusing on detection of a target sequence, such as infectious disease or GMO monitoring, the computational cost of analysis may be reduced by directly detecting the target sequence in the electrical signal instead. Here we present baseLess, a computational tool that enables such target-detection-only analysis. BaseLess makes use of an array of small neural networks, each of which efficiently detects a fixed-size subsequence of the target sequence directly from the electrical signal. We show that baseLess can accurately determine the identity of reads between three closely related fish species and can classify sequences in mixtures of twenty bacterial species, on an inexpensive single-board computer. Availability baseLess and all code used in data preparation and validation is available on Github at https://github.com/cvdelannoy/baseLess , under an MIT license. Used validation data and scripts can be found at https://doi.org/10.4121/20261392 , under an MIT license.

Authors 6

  1. Wageningen University & Research

    Affiliation as printed

    Bioinformatics Group, Wageningen University, Wageningen, The Netherlands

  2. Wageningen University & Research

    Affiliation as printed

    Marine Animal Ecology, Wageningen University, Wageningen, the Netherlands

  3. Leiden University · Consejo Superior de Investigaciones Científicas · Netherlands Institute of Ecology · Instituto de Hortofruticultura Subtropical y Mediterránea "La Mayora" · Universidad de Málaga

    Affiliation as printed

    Departamento de Microbiología, Instituto de Hortofruticultura Subtropical y Mediterránea “La Mayora”, Universidad de Málaga-Consejo Superior de Investigaciones Científicas (IHSM-UMA-CSIC), Málaga, Spain

    Department of Microbial Ecology, Netherlands Institute of Ecology, Wageningen, The Netherlands

    Institute of Biology, Leiden University, Leiden, The Netherlands

    Departamento de Microbiología, Instituto de Hortofruticultura Subtropical y Mediterránea "La Mayora", Universidad de Málaga-Consejo Superior de Investigaciones Científicas (IHSM-UMA-CSIC), Málaga, Spain

  4. Leiden University · Netherlands Institute of Ecology

    Affiliation as printed

    Department of Microbial Ecology, Netherlands Institute of Ecology, Wageningen, The Netherlands

    Institute of Biology, Leiden University, Leiden, The Netherlands

  5. Wageningen University & Research

    Affiliation as printed

    Bioinformatics Group, Wageningen University, Wageningen, The Netherlands

  6. Carlos Victor de Lannoy corresponding

    Wageningen University & Research · Delft University of Technology

    Affiliation as printed

    Bioinformatics Group, Wageningen University, Wageningen, The Netherlands

    Department of Bionanoscience, Delft University of Technology, Delft, The Netherlands

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References 21