CloudATAC: a cloud-based framework for ATAC-Seq data analysis

Area of Science:

• Epigenetics and Genomics
• Bioinformatics and Computational Biology
• Cloud Computing in Life Sciences

Background:

• Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) is crucial for genome-wide chromatin accessibility profiling.
• Analyzing ATAC-seq data involves complex, interdependent bioinformatics pipelines, posing a challenge for non-specialists.
• Limited computational resources often hinder comprehensive ATAC-seq data analysis.

Purpose of the Study:

• To present Cloud ATAC, an open-source, cloud-based framework for streamlined ATAC-seq data analysis.
• To provide an interactive learning platform for both pooled-cell and single-cell ATAC-seq data analysis using best practices.
• To leverage cloud computing for scalable, flexible, and accessible epigenetic data analysis.

Main Methods:

• Development of a cloud-based framework utilizing Google Cloud for on-demand computational resources.
• Integration of Jupyter Notebooks for interactive learning, code execution, and data visualization.
• Implementation of best practices for pooled-cell and single-cell ATAC-seq data processing and analysis.
• Leveraging GPU instances to accelerate single-cell ATAC-seq framework runtime.

Main Results:

• Cloud ATAC provides a scalable and flexible analysis framework for ATAC-seq data.
• The interactive Jupyter Notebook environment enhances user learning and data interpretation.
• GPU acceleration significantly reduces processing times for single-cell ATAC-seq analyses.
• Publicly available source code and data facilitate reproducibility and adoption.

Conclusions:

• Cloud ATAC democratizes complex ATAC-seq data analysis by providing an accessible, cloud-based solution.
• The framework supports both pooled-cell and single-cell ATAC-seq, catering to diverse research needs.
• This resource module, part of the NIGMS Sandbox, promotes cloud-based learning in bioinformatics.