Essential Documentation for the WGCNA Package in R

R Package Documentation

Explore valuable documentation and insights to make the most of the WGCNA package in R. Get ready to unlock the full potential of the WGCNA package!

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Basic details of the WGCNA package in R

At R Basics, our goal is to make it easy for you to find documentation about the WGCNA package. That’s why we’ve compiled all the key information in one place. Dive into the details below to understand how this package can improve your work.

Title: Weighted Correlation Network Analysis
Description: Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data as originally described in Horvath and Zhang (2005) and Langfelder and Horvath (2008) . Includes functions for rudimentary data cleaning, construction of correlation networks, module identification, summarization, and relating of variables and modules to sample traits. Also includes a number of utility functions for data manipulation and visualization.
Author: Peter Langfelder and Steve Horvath with contributions by Chaochao Cai, Jun Dong, Jeremy Miller, Lin Song, Andy Yip, and Bin Zhang
Maintainer: Peter Langfelder
License type: GPL (>= 2)

Technical details of the WGCNA package in R

R documentation also provides technical details of a package, including its dependencies, enhancements, and compilation requirements. Learning this information will help you master the WGCNA package.

Version: In R, a version refers to a specific release of a package and can be used to track changes. To find the version number of the WGCNA package in the R console, you can use the packageVersion("WGCNA") function.
Compilation requirements: Some R packages include internal code that must be compiled for them to function correctly. The WGCNA package has compilation requirements.
Required dependencies: A required dependency refers to another package that is essential for the functioning of the main package. The WGCNA package has the following required dependencies: R (>= 3.0), dynamicTreeCut (>= 1.62), fastcluster.
Suggested dependencies: A suggested dependency adds extra features to the main package, but the main package can work without it. The WGCNA package has the following suggested dependencies: org.Hs.eg.db, org.Mm.eg.db, infotheo, entropy, minet.
External dependencies: External dependencies are other packages that the main package depends on for linking at compile time. The WGCNA package uses the following external sources: Rcpp.
Imported packages: Importing packages allows developers to leverage existing code and functionalities without having to reinvent the wheel. The WGCNA package has the following imported packages: stats, grDevices, utils, matrixStats (>= 0.8.1), Hmisc, impute, splines, foreach, doParallel, preprocessCore, survival, parallel, GO.db, AnnotationDbi, Rcpp (>= 0.11.0).
Enhancements: Enhancements help developers expand the capabilities of their packages without starting from scratch. The WGCNA package has no enhancements.

Three data scientists looking at a laptop

Capabilities of the WGCNA package in R

R documentation provides comprehensive information about a package, including its functions, datasets, and vignettes. Exploring this information will help you make the most of the WGCNA package’s functionalities.

Functions: Functions play a crucial role in R packages. They allow you to perform specific tasks and computations efficiently. To identify the functions in the WGCNA package, you can use the ls("package:WGCNA") function.
Datasets: Many R packages include built-in datasets that you can use to familiarize yourself with their functionalities. To identify any built-in datasets in the WGCNA package, you can use the data(package = "WGCNA") function.
Vignettes: R vignettes are documents that include examples for using a package. To view the list of available vignettes you can use the vignette(package = "WGCNA") function. This code will display a list of available vignettes you can read.
Citation information: Citing R packages in your publications is important as it recognizes the contributions of the developers. To find the citation information for the WGCNA package in the R console, you can use the citation("WGCNA") function.

Getting help with the WGCNA package in R

If you have trouble using the WGCNA package in R, there are several ways to get help.

The help() function: R’s built-in help system is a handy tool to find documentation. You can use the help("WGCNA") function to retrieve detailed information, examples, and usage instructions.
The ? operator: The ? operator is a shortcut for the help() function. You can simply type ?WGCNA to quickly find documentation.
Discussion forums: Online forums are excellent platforms to ask questions, share knowledge, and troubleshoot issues. The most popular forums for R programmers are StackOverflow and Posit Community.

Generate R documentation code

Use R Basics’ code generator tool to effortlessly access essential documentation for the WGCNA package within your R environment.



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### Install the {Package} package if not already installed.
if (!require("{Package}")) {
install.packages("{Package}")
}

### Load the {Package} package.
library("{Package}")

### Find details of the {Package} package.
packageDescription("{Package}")

### Explore the capabilities of the {Package} package.
# List of functions
ls("package:{Package}")
# List of datasets
data(package = "{Package}")
# List of vignettes
vignette(package = "{Package}")
# Citation information
citation("{Package}")

### Get help with the {Package} package.
help(package = "{Package}")

Additional R package documentation resources

Explore our comprehensive resource guides related to various types of R documentation. These guides are valuable resources for accessing a wide range of information, making it easier to navigate R documentation in one place.

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