R package installation and execution

R Package Installation and Execution

Summary

Install an R package from a custom repository and verify successful execution through package loading and validation checks. This skill ensures the package meets build standards and can be reliably invoked in an R environment.

When to use

When you have a new or updated R package available via a non-CRAN repository (such as r-universe) and need to verify it installs cleanly, passes R-CMD-check compliance, and is ready for downstream workflow execution. Use this before attempting to run domain-specific analyses that depend on the package.

When NOT to use

• Package is already installed and loaded in your current session and you only need to use it (no installation step required).
• Package is already available on CRAN; use standard install.packages() without custom repos instead.
• You are working in a containerized environment (Docker or Singularity) where dependencies may be pre-built; prefer pulling the pre-built image.

Inputs

• R installation with network access
• Package repository URL (e.g., r-universe host)
• Package name and desired version (optional)

Outputs

• Installed R package in library path
• Loaded package namespace in R session
• R-CMD-check validation report (from CI badge or local run)
• Optional: example data files and minimal execution output

How to apply

Configure R to use the target repository URL in its package sources (via the repos parameter in install.packages()). Install the package using install.packages() and verify with library() that it loads without errors. If the package provides a secondary setup function (e.g., tima::install_tima()), invoke it to ensure all optional dependencies are available. Confirm that the package has passed R-CMD-check on its CI pipeline (check the README badge or GitHub Actions workflow). Load example data if available (e.g., via tima::get_example_files()) and attempt a minimal function call to confirm runtime execution succeeds.

Related tools

• r-universe (Package repository hosting the compiled R package binaries and source) — https://taxonomicallyinformedannotation.r-universe.dev/tima
• R-CMD-check (Automated validation workflow that verifies package compliance with CRAN submission standards) — https://github.com/taxonomicallyinformedannotation/tima/actions/workflows/R-CMD-check.yaml
• GitHub Actions (CI/CD platform that runs R-CMD-check on commits and publishes status badge) — https://github.com/taxonomicallyinformedannotation/tima
• Docker (Optional containerized environment with pre-installed R package and all dependencies) — https://hub.docker.com/r/adafede/tima-r/

Examples

install.packages('tima', repos = c('https://taxonomicallyinformedannotation.r-universe.dev', 'https://bioconductor.org/packages/release/bioc', 'https://cloud.r-project.org')); tima::install_tima(); library(tima); tima::get_example_files()

Evaluation signals

• Package loads in R session with no errors or warnings when invoked as library(package_name)
• R-CMD-check badge in repository README shows passing status (green badge), indicating compliance with CRAN submission checklist
• Example data can be retrieved via the package's helper function (e.g., tima::get_example_files()) without file-not-found or permission errors
• A minimal function call from the package (e.g., validate_inputs() or equivalent) executes successfully and produces expected output structure
• Package namespace and exported functions are visible when running ls('package:package_name') or similar introspection

Limitations

• Package lifecycle is 'experimental' (as indicated by lifecycle badge), meaning API and behavior may change without deprecation notice in future releases.
• Secondary dependency installation via a helper function (e.g., tima::install_tima()) may fail if upstream package repositories are unavailable or if system-level dependencies (e.g., build tools, system libraries) are not present.
• Custom column names in input files are configurable but require manual parameter specification; mismatched column names will cause runtime errors, not installation errors.
• No changelog is published in the repository, so version-to-version breaking changes may not be documented; users must inspect GitHub commit history or release notes to track changes.

Evidence

• [readme] Installation method and repository configuration: "install.packages( "tima", repos = c( "https://taxonomicallyinformedannotation.r-universe.dev", "https://bioconductor.org/packages/release/bioc", "https://cloud.r-project.org" ) )"
• [readme] Secondary dependency setup function: "Then, you should be able to install the rest with:

tima::install_tima()
```"
- [readme] Package loading verification: "Load the installed package into the R environment using library(tima) and confirm no errors occur."
- [readme] R-CMD-check validation workflow: "Run R-CMD-check on the installed package to validate against the CRAN submission checklist and verify all tests pass as indicated by the CI badge in the README."
- [readme] Example data retrieval for verification: "In case you do not have your data ready, you can obtain some example data using:

``` r
tima::get_example_files()
```"
- [readme] Lifecycle and experimental status: "[![Lifecycle:
experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)]"