Abstract Motivation Modern computational biology relies heavily on command-line tools that underpin analytical workflows, yet integrating these tools into R-based analyses poses substantial challenges for reproducibility, especially for researchers with limited computational expertise. While R excels at statistical analysis and visualization, its native capabilities for executing external commands remain rudimentary, lacking structured integration, environment management, and reliable cross-platform support. Results To address these limitations, BLIT, an R package, provides a unified framework for seamless command-line integration within R, enabling R users to invoke external tools in an intuitive manner. Rather than positioning itself as yet another workflow manager, BLIT emphasizes the robust encapsulation and coordination of command-line tools, enabling users to construct reproducible analysis pipelines without leaving the R environment. BLIT encapsulates command-line programs as R6 objects with dynamic validation, Micromamba-based environment management, and native piping support. This makes BLIT a direct bridge between R scripts and heterogeneous command-line ecosystems, replacing fragile system() calls with a robust, standardized framework that supports conditional execution and single-machine parallel computing, with the capability to hand off constructed command workflows to HPC schedulers or workflow engines for large-scale execution. Although designed for bioinformatics, BLIT offers a general, platform-agnostic solution for constructing reproducible analytical pipelines within R. Availability and implementation BLIT is available on CRAN (https://cran.r-project.org/package=blit) and on GitHub (https://github.com/WangLabCSU/blit).
Ding et al. (Sat,) studied this question.