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Updated: Jan 14, 2026
A Versatile Automated Platform for Micro-scale Cell Stimulation Experiments
Published on: August 6, 2013
ShortCake: an integrated platform for efficient and reproducible single-cell analysis
Ryuichiro Nakato1, Luis Augusto Eijy Nagai1
1Laboratory of Computational Genomics, Institute for Quantitative Biosciences, The University of Tokyo, Tokyo 113-0032, Japan.
Summary:
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.
Availability And Implementation:
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).
