ShortCake: An integrated platform for efficient and reproducible single-cell analysis

TL;DR

ShortCake is a containerized platform that simplifies single-cell analysis workflows by integrating multiple tools in R and Python, ensuring reproducibility and reducing setup time.

Contribution

It introduces a unified, environment-isolated platform that seamlessly combines diverse single-cell analysis tools within Jupyter notebooks.

Findings

Streamlines single-cell analysis workflows.

Reduces environment setup time.

Enhances reproducibility of analyses.

Abstract

Motivation: Recent advances in single-cell analysis have introduced new computational challenges. Researchers often need to use multiple analysis tools written in different programming languages while managing version conflicts between related packages within a single workflow. For the research community, minimizing the time spent on environment setup and installation issues is essential. Results: We present ShortCake, a containerized platform that integrates a suite of single-cell analysis tools written in R and Python. ShortCake isolates competing Python tools into separate virtual environments that can be easily accessed within a Jupyter notebook. This enables users to effortlessly transition between various environments, including R, even within a single notebook. Additionally, ShortCake offers multiple ``flavors,'' enabling users to select container images tailored to their specific needs. ShortCake provides a unified environment with fixed versions of various tools, thus streamlining workflows, reducing setup time, and improving reproducibility. Availability and implementation: The ShortCake image is available on DockerHub (https://hub.docker.com/r/rnakato/shortcake). The source code is available on GitHub (https://github.com/rnakato/ShortCake).