pyrpipe

pyrpipe provides a Python framework to construct, execute, and report reproducible RNA-Seq analysis workflows for transcriptomic studies.

Key Features:

• Object-Oriented Framework: Enables construction of computational pipelines in an object-oriented manner for modular workflow assembly.
• High-Level APIs: Exposes high-level Python APIs to invoke a wide range of popular RNA-Seq tools from within Python.
• Customization and Extensibility: Allows incorporation of new Python code, third-party programs, and additional Python libraries, supports creation of pipeline checkpoints, and integrates with workflow management systems for execution across diverse computing environments.
• Reproducibility and Debugging: Supports reproducible RNA-Seq analyses and simplifies debugging of computational pipelines.
• Detailed Reporting: Generates comprehensive analysis and benchmark reports suitable for inclusion in scientific publications.
• Implementation and Environment: Implemented for Python 3.6+ and compatible with local and high-performance computing (HPC) environments.

Scientific Applications:

• GTEx analyses: Applied to GTEx (Genotype-Tissue Expression) datasets to analyze tissue-specific gene expression patterns.
• SARS-CoV-2 host response: Applied to RNA-Seq from SARS-CoV-2-infected human cells to analyze host transcriptional responses.
• Zea mays (maize) transcriptomics: Applied to Zea mays (maize) RNA-Seq datasets for plant transcriptome and regulatory mechanism studies.

Methodology:

Constructs object-oriented pipelines, provides high-level APIs to call external RNA-Seq tools from Python, supports pipeline checkpoints and integration with workflow management systems, and produces analysis and benchmark reports.