ReproPhylo: An Environment for Reproducible Phylogenomics

Area of Science:

• Computational Biology
• Bioinformatics
• Genomics

Background:

• Reproducibility is crucial for scientific integrity, especially in data-intensive fields like phylogenomics.
• Accurate reporting of analyses is essential for validating research findings.

Purpose of the Study:

• To introduce ReproPhylo, a novel phylogenomic analysis environment.
• To enhance experimental reproducibility and facilitate large-scale data handling in phylogenetics.
• To support methodological experimentation and exploration of parameters and data.

Main Methods:

• ReproPhylo stores experimental workflows as serialized Python objects, capturing provenance and environment details.
• The system integrates with Git for automatic version control and management of analysis iterations.
• Outputs include human-readable reports and comprehensive experimental archives suitable for publication.

Main Results:

• ReproPhylo ensures built-in, automatic reproducibility without user configuration.
• The 'single file' approach guarantees persistence of provenance across analysis updates.
• Facilitates thorough exploration of parameters and data, enhancing scientific rigor.

Conclusions:

• ReproPhylo provides a robust solution for reproducible phylogenomic analyses.
• The environment simplifies data handling and supports in-depth methodological experimentation.
• Designed for broad accessibility, ReproPhylo is platform-independent and offers multiple installation options.