About Customized R
scCustomize is a collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using R.
See accompanying scCustomize website for detailed tutorials of all aspects of scCustomize functionality.
scCustomize can be installed from CRAN on all platforms. For more detailed instructions see Installation.
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6 FAQs about [Customized R]
How to create a package in R?
The process of creating a usable package in R has several parts: Write the function (s) to include in the package. Create the documentation for the function (s) in the package. Build the package. (Optional, and not covered here) Publish the package. The first step is covered above with my sortby () function.
How do I Create A R package in RStudio?
Open a new project in RStudio. Go to the `File' menu and click on `New Project.' Then select `New Directory,' and `R Package' to create a new R package. 5. Type the name of your package, then upload the .R le you created in step 1 under `Create package based on source les'. Click `Create project.' 6.
How do I Make my R package accessible to everyone?
To make your package easily accessible for everyone, there are two basic strategies. You can either publish your package on GitHub (which, in terms of transparency, is always a good idea) or you can submit it to the Comprehensive R Archive Network (CRAN). Both offer the ability for others to use your package but differ in several important aspects.
How does R install work?
The R INSTALL facilities check if the version of R used is recent enough for the package being installed, and the list of packages which is specified will be attached (after checking version requirements) before the current package.
Why do we need R packages?
R packages are a great way to encourage code reuse and provide a vehicle to document and package our work so that we can extend the life of our code beyond our own projects. Campbell, M. (2019).
Why should I use a package format in R?
Problems that have been solved in R and can be coded in a way that is generally useful are good candidates for packages. You may also want to create packages that only really apply to your own team or you own projects. The reason is that coding in a package format encourages code reuse and process efficiency.
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