Molecular Precision Oncology Program, National Center for Tumor Diseases (NCT).
Heidelberg Institute of Stem Cell Technology and Experimental Medicine (HI-STEM).
Bioinformatics. 2022 Sep 2;38(17):4248-4251. doi: 10.1093/bioinformatics/btac449.
Numerous R packages have been developed for bioinformatics analysis in the last decade and dependencies among packages have become critical issues to consider. In this work, we proposed a new metric named dependency heaviness that measures the number of dependencies that a parent uniquely brings to a package and we proposed possible solutions for reducing the complexity of dependencies by optimizing the use of heavy parents. We implemented the metric in a new R package pkgndep which provides an intuitive way for dependency heaviness analysis. Based on pkgndep, we additionally performed a global analysis of dependency heaviness on CRAN and Bioconductor ecosystems and we revealed top packages that have significant contributions of high dependency heaviness to their child packages.
The package pkgndep and documentations are freely available from the Comprehensive R Archive Network https://cran.r-project.org/package=pkgndep. The dependency heaviness analysis for all 22 076 CRAN and Bioconductor packages retrieved on June 8, 2022 are available at https://pkgndep.github.io/.
Supplementary data are available at Bioinformatics online.
在过去的十年中,已经开发了许多用于生物信息学分析的 R 包,包之间的依赖关系已成为需要考虑的关键问题。在这项工作中,我们提出了一个新的度量标准,称为依赖繁重度,用于衡量父包为子包带来的独特依赖数量,并提出了通过优化重父包的使用来降低依赖复杂性的可能解决方案。我们在一个名为 pkgndep 的新 R 包中实现了该度量标准,该包提供了一种直观的依赖繁重度分析方法。基于 pkgndep,我们还对 CRAN 和 Bioconductor 生态系统中的依赖繁重度进行了全局分析,并揭示了对其子包具有高依赖繁重度重大贡献的顶级包。
pkgndep 包及其文档可从 Comprehensive R Archive Network https://cran.r-project.org/package=pkgndep 免费获得。2022 年 6 月 8 日检索到的所有 22076 个 CRAN 和 Bioconductor 包的依赖繁重度分析可在 https://pkgndep.github.io/ 上获得。
补充数据可在 Bioinformatics 在线获得。