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Updated: Nov 12, 2025

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
Published on: May 28, 2021
biogitflow: development workflow protocols for bioinformatics pipelines with git and GitLab.
Choumouss Kamoun1,2,3,4, Julien Roméjon1,2,3,4, Henri de Soyres1,2,3,4
1Institut Curie, Paris, F-75005, France.
This study introduces git and GitLab-based protocols for developing bioinformatics pipelines, ensuring reproducible workflows for diagnostic and theranostic decision support. These guidelines streamline feature development and bug fixing in healthcare bioinformatics.
Area of Science:
- Bioinformatics
- Software Engineering
- Computational Biology
- Health Informatics
Background:
- Bioinformatics pipelines are crucial for diagnostic and theranostic decisions in healthcare.
- A standardized development workflow is essential for reliable and reproducible bioinformatics tools.
- Existing software engineering practices can be adapted to improve bioinformatics pipeline development.
Purpose of the Study:
- To define detailed development workflow guidelines for bioinformatics pipelines.
- To implement protocols supporting diagnostic and theranostic decision-making processes.
- To provide a reproducible framework for bioinformatics software development.
Main Methods:
- Implementation of step-by-step protocols using git and GitLab.
- Adoption of the gitflow branching model for structured development.
- Definition of protocols for nominal feature development and hotfix bug correction.
Main Results:
- Developed comprehensive protocols for bioinformatics pipeline development.
- Established clear guidelines for command lines and developer actions.
- Successfully addressed use cases for new feature integration and production bug fixes.
Conclusions:
- The implemented protocols enhance the reliability and reproducibility of bioinformatics pipelines.
- Git-based workflows facilitate efficient development and maintenance of healthcare bioinformatics tools.
- The documented protocols serve as a valuable resource for bioinformatics developers.
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