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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.

Bioinformatics (Oxford, England)
|October 23, 2025
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Summary
This summary is machine-generated.

ShortCake is a containerized platform that simplifies single-cell analysis by integrating R and Python tools. It resolves computational challenges, reduces setup time, and enhances reproducibility for researchers.

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Area of Science:

  • Computational biology
  • Bioinformatics
  • Genomics

Background:

  • Single-cell analysis presents computational challenges due to diverse tools and programming languages.
  • Managing package versions and environment setup hinders research reproducibility and efficiency.

Purpose of the Study:

  • To present ShortCake, a containerized platform designed to streamline single-cell analysis workflows.
  • To address challenges in integrating R and Python tools and managing dependencies.

Main Methods:

  • Developed ShortCake as a containerized platform integrating R and Python single-cell analysis tools.
  • Implemented isolated virtual environments for competing Python tools within Jupyter notebooks.
  • Offered multiple container image 'flavors' for tailored user needs.

Main Results:

  • ShortCake provides a unified environment with fixed tool versions, simplifying complex workflows.
  • Users can seamlessly transition between R and Python environments within a single notebook.
  • Reduced time spent on environment setup and installation issues.

Conclusions:

  • ShortCake enhances reproducibility in single-cell analysis by providing a stable, integrated environment.
  • The platform minimizes computational hurdles, allowing researchers to focus on biological insights.
  • ShortCake facilitates efficient and reliable execution of multi-language single-cell analysis pipelines.