pyrpipe: a python package for RNA-Seq workflows

Singh, Urminder; Li, Jing; Seetharam, Arun; Wurtele, Eve Syrkin

The availability of terabytes of RNA-Seq data and continuous emergence of new analysis tools, enable unprecedented biological insight. However, implementing RNA-Seq analysis pipelines in a reproducible, flexible manner is challenging as data gets bigger and more complex. Thus, there is a pressing requirement for frameworks that allows for fast, efficient, easy-to-manage, and reproducibile analysis. Simple scripting has many challenges and drawbacks. We have developed a python package, python RNA-Seq Pipeliner (pyrpipe) that enables straightforward development of flexible, reproducible and easy-to-debug computational pipelines purely in python, in an object-oriented manner. pyrpipe provides access to popular RNA-Seq tools, within python, via easy-to-use high level APIs. Pipelines can be customized by integrating new python code, third-party programs, or python libraries. Users can create checkpoints in the pipeline or integrate pyrpipe into a workflow management system, thus allowing execution on multiple computing environments. pyrpipe produces detailed analysis, and benchmark reports which can be shared or included in publications. pyrpipe is implemented in python and is compatible with python versions 3.6 and higher. To illustrate the rich functionality of pyrpipe, we provide case studies using RNA-Seq data from GTEx, SARS-CoV-2-infected human cells, and Zea mays. All source code is freely available at https://github.com/urmi-21/pyrpipe; the package can be installed from the source or from PyPI (https://pypi.org/project/pyrpipe). Documentation is available at (http://pyrpipe.rtfd.io).