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Abstract

Among the available Linux container technologies, Docker is one of the most popular ones. Docker images can be used to provide ready-to-use software packages, where all required dependencies are already installed, and they can be deployed in any operating system where Docker is installed. They are also a convenient way to store immutable working software packages, thus contributing to reproducibility. Moreover, the usage of Docker images greatly eases the development of complex pipelines, standalone software applications with graphical user interfaces that require external software, and even the development of databases. Therefore, not surprisingly, Docker images are now ubiquitously used in computational biology and bioinformatics. Here, we present the pegi3s Bioinformatics Docker Images Project (https://pegi3s.github.io/dockerfiles/), a collection of more than 70 Docker images for commonly used software in the fields of genomics, transcriptomics, proteomics, phylogenetics, and sequence handling, among others, that is constantly growing. Several features distinguish this project from much larger projects, namely: 1) by providing a list of tools that are classified into broad categories, it is easier to find the most adequate tool(s) for a given project; 2) by providing the hyperlinks to the software manuals, we facilitate the process of finding the parameter combinations that are best suited for a given processing step; 3) most importantly, we provide clear instructions on how to run the images, provide test data that can be used to quickly evaluate the Docker image, and give all details on how each Docker image was built. All images are routinely used by ourselves, in the context of our research and teaching activities, meaning that they have been extensively tested. Therefore, we believe that this project, which is offered as a service in the context of the European ELIXIR program, is of interest to many researchers, independently of having or not a background in informatics.

H. López-Fernández and P. Ferreira—Contributed equally to this work.

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Notes

  1. 1.

    https://www.winehq.org.

  2. 2.

    https://pegi3s.github.io/dockerfiles.

  3. 3.

    https://hub.docker.com.

  4. 4.

    http://bioboxes.org.

  5. 5.

    https://biocontainers.pro.

  6. 6.

    https://dugongbioinformatics.github.io.

  7. 7.

    https://dockstore.org.

  8. 8.

    http://www.reproducible-bioinformatics.org.

  9. 9.

    https://hub.docker.com/r/bcgsc/orca.

  10. 10.

    https://www.sing-group.org/seda/manual/operations.html#splign-compart-pipeline.

  11. 11.

    https://docs.docker.com/docker-for-windows/install.

  12. 12.

    https://github.com/pegi3s/dockerfiles/blob/master/tutorials/singularity.md.

  13. 13.

    https://xpra.org.

  14. 14.

    https://github.com/docker-java/docker-java.

  15. 15.

    https://github.com/sing-group/evoppi-docker.

  16. 16.

    https://ubuntu.com/about.

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Acknowledgments

This work was financed by the National Funds through FCT—Fundação para a Ciência e a Tecnologia, I.P., under the project UIDB/04293/2020 and through the individual scientific employment program-contract with Hugo López-Fernández (2020.00515.CEECIND), and also by BioData.pt (project 22231/01/SAICT/2016). This work was also partially supported by the Consellería de Educación, Universidades e Formación Profesional (Xunta de Galicia) under the scope of the strategic funding ED431C2018/55-GRC Competitive Reference Group.

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López-Fernández, H., Ferreira, P., Reboiro-Jato, M., Vieira, C.P., Vieira, J. (2022). The pegi3s Bioinformatics Docker Images Project. In: Rocha, M., Fdez-Riverola, F., Mohamad, M.S., Casado-Vara, R. (eds) Practical Applications of Computational Biology & Bioinformatics, 15th International Conference (PACBB 2021). PACBB 2021. Lecture Notes in Networks and Systems, vol 325. Springer, Cham. https://doi.org/10.1007/978-3-030-86258-9_4

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