snakePipes: facilitating flexible, scalable and integrative epigenomic analysis

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• The increasing volume and complexity of epigenomic data necessitate efficient and adaptable analysis tools.
• Existing workflows may lack modularity and scalability, hindering comprehensive analysis of diverse epigenomic assays.

Purpose of the Study:

• To introduce snakePipes, a versatile workflow package designed for the processing and downstream analysis of multiple epigenomic data types.
• To provide a user-friendly solution for assembling custom analysis workflows and managing underlying bioinformatics tools.

Main Methods:

• Development of a workflow package named snakePipes.
• Implementation of command-line wrappers and YAML files for workflow customization and tool management.
• Support for common epigenomic assays: ChIP-seq, RNA-seq, Bisulfite-seq, ATAC-seq, Hi-C, and single-cell RNA-seq.

Main Results:

• snakePipes provides a unified framework for analyzing diverse epigenomic data.
• The package facilitates easy installation and upgrading of essential bioinformatics tools.
• Users can readily assemble customized analysis pipelines tailored to their specific research needs.

Conclusions:

• snakePipes addresses the need for modular and scalable analysis of large-scale epigenomic data.
• The package empowers researchers to efficiently process and analyze data from various epigenomic assays.
• snakePipes enhances the accessibility and reproducibility of epigenomic data analysis.