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

Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) generates genome-wide chromatin accessibility profiles, providing valuable insights into epigenetic gene regulation at both pooled-cell and single-cell population levels. Comprehensive analysis of ATAC-seq data involves the use of various interdependent programs. Learning the correct sequence of steps needed to process the data can represent a major hurdle. Selecting appropriate parameters at each stage, including pre-analysis, core analysis, and advanced downstream analysis, is important to ensure accurate analysis and interpretation of ATAC-seq data. Additionally, obtaining and working within a limited computational environment presents a significant challenge to non-bioinformatic researchers. Therefore, we present Cloud ATAC, an open-source, cloud-based interactive framework with a scalable, flexible, and streamlined analysis framework based on the best practices approach for pooled-cell and single-cell ATAC-seq data. These frameworks use on-demand computational power and memory, scalability, and a secure and compliant environment provided by the Google Cloud. Additionally, we leverage Jupyter Notebook's interactive computing platform that combines live code, tutorials, narrative text, flashcards, quizzes, and custom visualizations to enhance learning and analysis. Further, leveraging GPU instances has significantly improved the run-time of the single-cell framework. The source codes and data are publicly available through NIH Cloud lab https://github.com/NIGMS/ATAC-Seq-and-Single-Cell-ATAC-Seq-Analysis. This manuscript describes the development of a resource module that is part of a learning platform named ``NIGMS Sandbox for Cloud-based Learning'' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.

Whole-genome bisulfite sequencing data analysis learning module on Google Cloud Platform.

This study describes the development of a resource module that is part of a learning platform named 'NIGMS Sandbox for Cloud-based Learning' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module is designed to facilitate interactive learning of whole-genome bisulfite sequencing (WGBS) data analysis utilizing cloud-based tools in Google Cloud Platform, such as Cloud Storage, Vertex AI notebooks and Google Batch. WGBS is a powerful technique that can provide comprehensive insights into DNA methylation patterns at single cytosine resolution, essential for understanding epigenetic regulation across the genome. The designed learning module first provides step-by-step tutorials that guide learners through two main stages of WGBS data analysis, preprocessing and the identification of differentially methylated regions. And then, it provides a streamlined workflow and demonstrates how to effectively use it for large datasets given the power of cloud infrastructure. The integration of these interconnected submodules progressively deepens the user's understanding of the WGBS analysis process along with the use of cloud resources. Through this module, we can enhance the accessibility and adoption of cloud computing in epigenomic research, speeding up the advancements in the related field and beyond. This manuscript describes the development of a resource module that is part of a learning platform named ``NIGMS Sandbox for Cloud-based Learning'' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.