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.

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Coding Club: Creating an R Package

3.1 Function Overview. First, let''s create a very basic function to learn about custom functions. Functions need a name (like any R object).They are created with the function() function. We''re going to make a function that rounds numbers and keeps the trailing zeroes, so let''s call it round0.

Customized Research » IT''IS Foundation

Customized Research: R&D Services. The IT''IS Foundation offers integrated, in-house scientific/engineering and regulatory capabilities to facilitate the translation of scientific discoveries into immediate and long-term solutions for partners in

1 Creating R packages – R Manuals :: Writing R Extensions

Packages provide a mechanism for loading optional code, data and documentation as needed. The R distribution itself includes about 30 packages. In the following, we assume that you

Creating a Custom R Package

Create Custom Layouts in Your R Plots When plotting data, we''re generally trying to create a single plot. But what do you do if you want to create a single presentation of a set

Creating Your First R Package in 2 Minutes in RStudio!

Creating an R package is easier than you may think! Here we create a simple package that contains the minimum file structure, a custom function, and a help f...

1 Creating R packages – R Manuals :: Writing R Extensions

A directory into which packages are installed, e.g. /usr/lib/R/library: in that sense it is sometimes referred to as a library directory or library tree (since the library is a directory which contains packages as directories, which themselves contain directories). That used by the operating system, as a shared, dynamic or static library or (especially on Windows) a DLL, where the

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Custom Visualizations & Functions for Streamlined Analyses of

scCustomize is an R package with collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using R.

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Customizing your package-library location

For reasonably experienced R users this simple topic might not seem worthy of a blog post, so if you are not an R beginner, you may want to skip this post. Having that said, I have had to explain this task so many times on R community forums that writing one becomes mandatory to avoid typing the same text yet once again. The reasons to customize your library path instead of

How to write your own R package and publish it on CRAN

R packages come in various shapes — from entire universes such as the tidyverse package family (if you look for some Stata like feedback when using the tidyverse

How to create your own functions in R

We''ve talked a lot about how to use different pre-made functions in R, but sometimes you just need to make your own function to tackle your data. This could be really useful for shortening the names in a list of species — writing a custom function makes the process much easier. Functions without arguments. You can also create functions

How to Make Beautiful Tables in R

Learn more about gtextras. kable + kableExtra. The kableExtra package builds on the kable output from the knitr package.As author Hao Zhu puts it: The goal of kableExtra is to help you build common complex tables and manipulate table styles imports the pipe %>% symbol from magrittr and verbalize all the functions, so basically you can add "layers" to a

Building your own R Package

We will use devtools package to create an appropriate package structure and perform frequent development tasks, like building, installing, and loading the package, checking and updating its documentation, run examples and tests.. Devtools package contains the following core functions: create() document() check() build() test() R package roxygen2 will help us to

Custom R scripts

Custom R scripts. Customized functions in the R programming language for data analysis and visualization. Background: Often, I have to do the same tasks in R, especially when it comes to data visualization. Rather than re-write the same things over and over again, I

Community Ecology Book. Custom R functions

On this page find a summary of the custom R commands developed during production of the book. These are mentioned throughout the text and are available as part of the associated data file (see: Support Files).See also the

Instructions for Creating Your Own R Package

8.Open a new R script and write the code for your functions. In the same le, run package.skeleton(name = "mynewpackage"), inserting the name of your package in the name argument. This will create a new folder in the directory you found in step 6. 9.Navigate to this directory (C:nUsersnNinanDocuments"). You should see a folder with the

Schrödinger Notes—Enumeration Tools for Library Design

In addition to using the 13 pre-packaged R-groups libraries, you can generate or import your own custom R-group libraries. R-groups can be added using a sketcher or they can be defined from a Maximum Common Substructure analysis of a set of ligands. These libraries can then be used in the Custom R-Group Enumeration panel, as shown in Section 2.

Custom-R

This channel was originally dedicated to F-Zero Custom Tracks but has since expanded to do more than cover F-Zero games in depth. Content from games such as Super Pilot, Hot Wheels Unleashed, Hot

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Custom sorting of a dataframe in R. 0. Sorting within each category separately in R. 0. Customised ordering according to column data in R. 1. R: Sorting with a predetermined order. 0. customize the sort function in R. 1. Sorting rows into non-alphabetical customized order. 0. Partial/Custom sorting in R vector. 2.

Where in R do I permanently store my custom functions?

The accepted answer is best long-term: Make a package. Luckily, the learning curve for doing this has been dramatically reduced by the devtools package: It automates package creation (a nice assist in getting off on the right foot), encourages good practices (like documenting with roxygen2, and helps with using online version control (bitbucket, github or

R Packages (2e)

Welcome to the online version of the 2nd edition of "R Packages" by Hadley Wickham and Jennifer Bryan. Packages are the fundamental units of reproducible R code. They include reusable R functions, the documentation that describes how to use them, and sample data.

Custom Visualizations & Functions for Streamlined Analyses of

Collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using R. scCustomize aims to provide 1) Customized visualizations for aid in ease of use and to create more aesthetic and functional visuals. 2) Improve speed/reproducibility of common tasks/pieces of code in scRNA-seq analysis with a single or group of functions. For citation

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How to Write Functions in R (with 18 Code Examples)

A function in R is an object containing multiple interrelated statements that are run together in a predefined order every time the function is called. Functions in R can be built-in or created by the user (user-defined). The main purpose of creating a user-defined function is to optimize our program, avoid the repetition of the same block of

Custom Packages in R: A Step-by-Step Tutorial

R is a powerful and flexible programming language for data analysis and visualization.One of the advantages of R is that it allows users to create and share their packages, which are collections of functions, data, and documentation that can extend the functionality of R. Creating your R package can help you organize your code, reuse your functions, and share

Best RStudio themes [CHANGE, ADD and CREATE]

Choosing one you will be able to see a preview (although not in R code) and customize all the color scheme in the theme editor. Once done, you can change the theme name in Info tab, download the .tmtheme file and add it to RStudio. Share your

How to Customize your RStudio Theme (Finally)

Ability to run R jobs in the background; More SQL functionality; Cool plumbr API tools; But for us, the sweetest feature is the ability to import our own themes! This article will quickly run through how we can duplicate the

About Customized R

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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