BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters
- Published
- Accepted
- Subject Areas
- Bioinformatics, Computational Biology, Genomics, Microbiology
- Keywords
- Docker, pan-genome, biosynthetic gene clusters, Bacillus amyloliquefaciens
- Copyright
- © 2017 Cheng et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2017. BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters. PeerJ Preprints 5:e3040v1 https://doi.org/10.7287/peerj.preprints.3040v1
Abstract
Recently, Docker technology has received increasing attention throughout the bioinformatics community. However, its implementation has not yet been mastered by most biologists, and thus its application in biological research has been limited. In order to popularize this technology in the field of bioinformatics and promote the use of publicly available bioinformatics tools, such as Dockerfiles and Images from communities, governmental, and private owners in Docker Hub Registry and other Docker-based resources, we introduce here a complete and accurate bioinformatics workflow based on Docker to analyze and visualize pan-genomes and biosynthetic gene clusters of bacteria. This provides a new solution for bioinformatics mining of big data from various public biological databases. This step-by-step guide creates an integrative workflow through a Dockerfile to allow researchers to build their own Image and run Container easily.
Author Comment
This is a submission to PeerJ for review.