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CREDO: a friendly Customizable, REproducible, DOcker file generator for bioinformatics applications.

Authors :
Alessandri, Simone
Ratto, Maria L.
Rabellino, Sergio
Piacenti, Gabriele
Contaldo, Sandro Gepiro
Pernice, Simone
Beccuti, Marco
Calogero, Raffaele A.
Alessandri, Luca
Source :
BMC Bioinformatics. 3/12/2024, Vol. 25 Issue 1, p1-16. 16p.
Publication Year :
2024

Abstract

Background: The analysis of large and complex biological datasets in bioinformatics poses a significant challenge to achieving reproducible research outcomes due to inconsistencies and the lack of standardization in the analysis process. These issues can lead to discrepancies in results, undermining the credibility and impact of bioinformatics research and creating mistrust in the scientific process. To address these challenges, open science practices such as sharing data, code, and methods have been encouraged. Results: CREDO, a Customizable, REproducible, DOcker file generator for bioinformatics applications, has been developed as a tool to moderate reproducibility issues by building and distributing docker containers with embedded bioinformatics tools. CREDO simplifies the process of generating Docker images, facilitating reproducibility and efficient research in bioinformatics. The crucial step in generating a Docker image is creating the Dockerfile, which requires incorporating heterogeneous packages and environments such as Bioconductor and Conda. CREDO stores all required package information and dependencies in a Github-compatible format to enhance Docker image reproducibility, allowing easy image creation from scratch. The user-friendly GUI and CREDO's ability to generate modular Docker images make it an ideal tool for life scientists to efficiently create Docker images. Overall, CREDO is a valuable tool for addressing reproducibility issues in bioinformatics research and promoting open science practices. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14712105
Volume :
25
Issue :
1
Database :
Academic Search Index
Journal :
BMC Bioinformatics
Publication Type :
Academic Journal
Accession number :
176005899
Full Text :
https://doi.org/10.1186/s12859-024-05695-9