SigBridgeR

---

🌐 Overview

SigBridgeR integrates multiple algorithms, using single-cell RNA sequencing data, bulk expression data, and sample-related phenotypic data, to identify the cells most closely associated with the phenotypic data, performing as a bridge to existing tools.

🔧 Installation

Usually we recommend installing the latest release from GitHub because of the latest features and bug fixes.

1. Install the development version from GitHub:

if (!requireNamespace("remotes")) {
  install.packages("remotes")
}
remotes::install_github("WangLabCSU/SigBridgeR")

2. Install from r-universe:

install.packages("SigBridgeR", repos = "https://wanglabcsu.r-universe.dev")

It is recommended to install the following packages to improve runtime speed.

install.packages("matrixStats")
install.packages("preprocessCore")

📓 Documentation

Get Started:

• A Quick Started Guide
• Full Tutorial for more details
• View Github Webpage
• Use ?SigBridgeR::function_name to access the help documents in R.

If you encounter problems, please see:

• Troubleshooting Guide
• Please use Github issues if you want to file bug reports or feature requests, let us know if you have ideas to make this project better!

Other information:

• What is Single Cell Sequencing?
  • Veiw in Wiki
• What is RNA-seq?
  • View in Wiki