A toolkit for ARB to integrate custom databases and externally built phylogenies

Area of Science:

• Bioinformatics
• Computational Ecology
• Genomics

Background:

• Biological sequence data is growing rapidly, posing computational challenges for ecologists.
• Current methods for data analysis (e.g., alignment, phylogeny) scale poorly with dataset size.
• Ecologists face a trade-off between expensive local hardware and cloud computing without direct data interaction.

Purpose of the Study:

• To develop a software solution that integrates desktop analytical tools with cloud-based computational power.
• To overcome the limitations of existing computational approaches for large biological datasets.
• To provide researchers with both high throughput and analytical capability.

Main Methods:

• A novel software package acting as middleware between desktop and cloud resources.
• Enables the creation of local custom databases with sequences and metadata.
• Facilitates linking of cloud-computed data back to local databases.

Main Results:

• The software leverages interactive desktop tools (like ARB) with cloud computing.
• It allows researchers to manage and analyze large biological sequence datasets more effectively.
• A tutorial implementation is available for practical application.

Conclusions:

• The developed pipeline mitigates the trade-off between computational throughput and analytical capability.
• It offers a more efficient and integrated approach for handling massive biological sequence data.
• Researchers can now benefit from both interactive exploration and powerful cloud computation.