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Packaging Biocomputing Software to Maximize Distribution and Reuse.

William S Bush1, Nicholas Wheeler, Brett Beaulieu-Jones

  • 1Cleveland Institute for Computational Biology, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA, wsb36@case.edu.

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Summary
This summary is machine-generated.

This tutorial introduces tools and methods for sharing computational biology software. It addresses common implementation challenges to improve software distribution and research reproducibility.

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Area of Science:

  • Computational biology
  • Biocomputing
  • Bioinformatics software development

Background:

  • Many computational biology papers present novel software.
  • Availability of source code is often required but not sufficient for broad adoption.
  • Implementation issues like configuration and version conflicts hinder software distribution and reproducibility.

Purpose of the Study:

  • To demonstrate tools and approaches for effective software packaging and distribution.
  • To provide best practices for open sharing of biocomputing software.
  • To overcome common barriers in computational biology software deployment.

Main Methods:

  • Utilizing modern software packaging and containerization techniques.
  • Applying best practices for version control and dependency management.
  • Demonstrating reproducible research workflows in biocomputing.

Main Results:

  • Improved methods for distributing computational biology software.
  • Reduced challenges related to system configuration and software compatibility.
  • Enhanced accessibility and usability of biocomputing tools for researchers.

Conclusions:

  • Effective software packaging and distribution are crucial for computational biology.
  • Adopting standardized practices can significantly improve research reproducibility.
  • Open sharing of biocomputing software facilitates scientific advancement.