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BiocPkgTools: Toolkit for mining the Bioconductor package ecosystem.

Shian Su¹, Vincent J Carey², Lori Shepherd³

¹Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia.

|June 29, 2019

Summary

This summary is machine-generated.

BiocPkgTools is a new R package providing computable metadata for the Bioconductor project, enabling easier data analysis and package discovery for large-scale biological data. It facilitates custom reporting, data mining, and graph analytics on package dependencies.

Keywords:

bioconductor bioinformatics r reproducible research software

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Area of Science:

Bioinformatics
Computational Biology
Software Engineering

Background:

The Bioconductor project is a rapidly expanding repository of open-source software for analyzing large-scale biological data.
There is a growing need for tools that provide accessible package metadata to both developers and users.
Efficiently managing and understanding the Bioconductor package ecosystem is crucial for its continued growth and utility.

Purpose of the Study:

To develop a software tool that exposes Bioconductor package metadata in a computable format.
To facilitate downstream applications such as custom reporting, data mining, and graph analytics.
To enhance package discovery and understanding within the Bioconductor ecosystem.

Main Methods:

Development of the BiocPkgTools R package.
Implementation of functions to load package metadata, download statistics, dependencies, and build reports in tidy data format.
Integration of capabilities for converting tidy data to graph structures for analytics and visualization.
Creation of a user-friendly graphical package explorer.

Main Results:

The BiocPkgTools package is integrated into the Bioconductor project and installs using standard R procedures.
Provides access to comprehensive package metadata, download statistics, dependencies, and build reports in tidy data format.
Enables graph-based analytics and visualization of package relationships.
Offers a graphical interface for intuitive package discovery.

Conclusions:

BiocPkgTools effectively provides computable metadata for the Bioconductor ecosystem.
The package supports diverse downstream applications, including data mining, reporting, and dependency analysis.
BiocPkgTools enhances the usability and discoverability of Bioconductor packages for researchers.