miCloud: A Plug-n-Play, Extensible, On-Premises Bioinformatics Cloud for Seamless Execution of Complex...

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Low-cost small-factor sequencers have increased access to genomics sequencing.
• Bioinformatics data analysis remains a significant bottleneck for many laboratories and clinical facilities.
• Lack of user-friendly software hinders the adoption of genomic sequencing for medical applications.

Purpose of the Study:

• To develop a user-friendly bioinformatics platform for genomic data analysis.
• To address the data analysis bottleneck in independent laboratories and small clinical facilities.
• To enable seamless integration of genomic sequencers with cloud-based data analysis.

Main Methods:

• Development of miCloud, a fully featured cloud-based bioinformatics platform.
• Integration of miCloud with genome sequencers over a local network.
• Deployment of miCloud on various computing environments without prior bioinformatics expertise.
• Provision of preconfigured RNA-Seq and CHIP-Seq pipelines.
• Support for developing or installing new tools from Docker container repositories.
• Integration with the Visual Omics Explorer framework for data visualization.

Main Results:

• miCloud enables easy deployment and use of genomic data analysis tools.
• The platform provides access to preconfigured bioinformatics pipelines for RNA-Seq and CHIP-Seq.
• Users can customize pipelines by installing additional tools from Docker repositories.
• Integrated visualizations and publication-ready graphics are generated from sequencing data.

Conclusions:

• miCloud standardizes genomic data analysis, similar to sample preparation kits in molecular biology.
• The platform facilitates the adoption of genomic sequencing in research and clinical settings.
• miCloud empowers researchers and clinicians with accessible and powerful bioinformatics capabilities.