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

## TL;DR

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

## Contribution

ShortCake introduces a unified, containerized environment with isolated virtual environments for single-cell analysis tools.

## Key findings

- ShortCake isolates Python tools into separate virtual environments accessible via Jupyter notebooks.
- The platform offers multiple container 'flavors' tailored to specific user needs.
- ShortCake reduces version conflicts and streamlines workflows for single-cell analysis.

## Abstract

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. 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.

The ShortCake image is available on DockerHub (https://hub.docker.com/r/rnakato/shortcake) and Zenodo (DOIs: 10.5281/zenodo.17116765 and 10.5281/zenodo.17118158). The source code is available on GitHub (https://github.com/rnakato/ShortCake).