![]() The specific MPN snapshot you want to install packages from (and any other repositories you may need).The required top level packages ( pkgr and MPN manage all of the dependencies).pkgr works by allowing you to write a single configuration file, pkgr.yml, where you specify: This tool allows you to define all aspects of your global environment with focus on two vital components of pharmacometric analysis, reproducibility and auditability. To help each collaborator on a project quickly identify and install all the packages relevant to a given project, MetrumRG developed a command line tool called pkgr. Furthermore, if you want to update your packages mid-project, you can simply update to a new snapshot that was curated to ensure all packages in that snapshot work well together. By installing packages from a specific MPN snapshot, rather than directly from CRAN, you can ensure it is always the same version of a given package. The Metrum Package Network, or MPN, was developed by MetrumRG to provide a repository of stable, curated snapshots of R packages (from CRAN and other repositories). ![]() This is achieved by installing the same versions of all R packages, a challenging task given the quantity, diversity, and interdependence of available packages. It's also important to future-proof your projects, so whether you run this code tomorrow or in a year's time, the output is the same and your code is not broken by changes in later package versions. ![]() To ensure a reproducible analysis environment, all project collaborators must work with the same versions of these packages. Modern approaches to running analyses with R increasingly rely on contributed packages that are not part of base R. This article will give you an overview of how to effectively manage packages in R using these tools. ![]() To address this, MetrumRG has developed a suite of tools that make R package management simple, easy, and reproducible, both within a single project and between multiple projects. Today, packages are highly interwoven and it is becoming increasingly difficult to manage the set of packages in a transparent and robust way. Managing R packages (and their dependencies) can be challenging and often frustrating. ![]()
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