Closha 2.0: a bio-workflow design system for massive genome data analysis on high performance cluster infrastructure

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Explosive growth in next-generation sequencing (NGS) data presents significant computational challenges.
• High costs and complexity of computational resources are barriers to big data analysis.
• Cloud computing offers a scalable solution for accessing necessary computational resources.

Purpose of the Study:

• To present Closha 2.0, a cloud-based service for analyzing large-scale genomic datasets.
• To provide an accessible platform for genomic researchers with varying levels of programming expertise.
• To enhance the usability and functionality of the previous Closha 1.0 version.

Main Methods:

• Development of a cloud computing service (Closha 2.0) with a user-friendly interface.
• Integration of a script editor supporting Python, R, and shell scripting.
• Implementation of containerization for tool execution to ensure stability and prevent conflicts.
• Inclusion of individual pipeline step execution for testing and parameter adjustment.
• Update of GBox for high-speed large dataset transmission.

Main Results:

• Closha 2.0 provides a stable, containerized environment for genomic data analysis.
• Users can integrate custom scripts and execute pipeline steps individually for flexibility.
• The platform simplifies complex analyses with drag-and-drop functionality.
• Reproducible analysis pipelines with permanently recorded parameters and inputs.
• Updated GBox facilitates efficient transfer of large genomic datasets.

Conclusions:

• Closha 2.0 offers a user-friendly, reproducible platform for genomic data analysis.
• The service empowers researchers to obtain accurate results from NGS data.
• Closha 2.0 is freely available, lowering barriers for genomic data analysis.