Bioinformatics software for genomic: a systematic review on GitHub
- Published
- Accepted
- Subject Areas
- Bioinformatics, Genomics, Computational Science
- Keywords
- Bioinformatics, open source genomics software, State-of-the-art technique, Mining Software Repositories, GitHub
- Copyright
- © 2018 Hidalgo Suarez 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
- 2018. Bioinformatics software for genomic: a systematic review on GitHub. PeerJ Preprints 6:e27352v3 https://doi.org/10.7287/peerj.preprints.27352v3
Abstract
Bioinformatics is an interdisciplinary field that develops software methods and tools to understand biological data. Actually, in branches such as genomics, there are a large number of software tools that serve to support different processes such as genetic data sequencing, genomes, biotechnological applications, among other activities, which contribute knowledge to different fields of study such as environment, medicine, energy and others. As a support to the area of genomics and specifically to the field of genomics, we describe and propose a method based on mining software repositories (MSR), which monitors, evaluates and maps the genomic software hosted in the GitHub. We use the VigHub tool to extract meta-data from projects and create visualizations on technological maps. We present a detailed systematic review of the genomic software projects on GitHub, where the highlights of the genomics area are shown. Specifically we show the technological maps of the programming languages most used in the creation of software. The Time-line, where software projects are displayed by category, relevance and programming languages as a function of time. Classification of the repositories by software categories and the most successful genomic software repositories in GitHub according to stars and score. This paper is aimed at bioinformatics researchers that require relevant information about the current state of a specific genomic technology found in GitHub. The method facilitates the identification of ideas, source code, specific data, platforms, applications, scripts and tools that support research and innovation in genomic software projects. The analysis provided in this paper allowed to identify software trends in the area, as well as new perspectives and future technologies.
Author Comment
It is necessary to integrate the acknowledgments into the document, so we made a new modification.
Supplemental Information
Justification of the paper
The rationale for conducting the meta-analysis; The contribution that the meta-analysis makes to knowledge in light of previously published related reports, including other meta-analyses and systematic reviews.