iRODS metadata management for a cancer genome analysis workflow

Area of Science:

• Genomics
• Bioinformatics
• Data Science

Background:

• Next-generation sequencing (NGS) generates massive datasets, presenting significant data security, storage, and metadata management challenges.
• Existing data analysis pipelines often do not adequately address these critical data management issues.

Purpose of the Study:

• To integrate the open-source Integrated Rule-Oriented Data System (iRODS) with a cancer genome analysis pipeline.
• To enhance data security, centralize storage, and unify metadata management for NGS data within a high-performance computing environment.

Main Methods:

• Integration of the iRODS metadata management system with a cancer genome analysis pipeline.
• Implementation in a high-performance computing environment.
• Development of a user-friendly front-end for metadata input and customized protection rules.

Main Results:

• A robust and efficient end-to-end workflow for NGS data management was established.
• The integrated system supports customized metadata attributes and fine-grained protection rules.
• Unified metadata information and enhanced data security were achieved.

Conclusions:

• Integrating iRODS with NGS data analysis pipelines effectively addresses key challenges in data security, storage, and metadata management.
• This approach provides a suitable solution for managing large-scale genomic datasets in research environments.