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![plot](inst/epiregulon_logo.png)<br> # Introduction Gene regulatory networks model the underlying gene regulation hierarchies that drive gene expression and cell states. The main function of the epiregulon package is to construct gene regulatory networks and infer transcription factor (TF) activity in single cells by integration of scATAC-seq and scRNA-seq data and incorporation of public bulk TF ChIP-seq data. For full documentation, please refer to the epiregulon [book]( ![plot](inst/epiregulon_schematics.svg) There are three related packages. The core epiregulon package supports `SingleCellExperiment` objects. If the users would like to start from `ArchR` projects, they may choose to use `epiregulon.archr` package, which allows for seamless integration with the [ArchR]( package. Moreover, we provide a suite of tools in `epiregulon.extra` package for enrichment analysis, visualization, and network analysis which can be run on the `epireglon` or `epiregulon.archr` output. # Installation ``` # install devtools if(!require(devtools)) install.packages("devtools") # install basic epiregulon package devtools::install_github(repo='xiaosaiyao/epiregulon') # install extended version of epiregulon devtools::install_github(repo='xiaosaiyao/epiregulon.archr') # install extended version of epiregulon devtools::install_github(repo='xiaosaiyao/epiregulon.extra') ``` Example data included in the tutorial are available from [scMultiome]( ``` if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("scMultiome") ``` # System Requirements ## Hardware Requirements The epiregulon package has been tested on a standard MacBook with 16GB of RAM and 8 cores ## Software Requirements The epiregulon package is supported for macOS, Linux and Windows. The package has been tested on the following systems: - macOS: Monterey (12.7.1) - Linux: Ubuntu 22.04.2 LTS - Windows: Windows 2022 Users should have R version 4.3.0 or higher # Functions Functions in the suite of Epiregulon packages ![plot](inst/epiregulon_functions.png) # Reference Tomasz Włodarczyk, Aaron Lun, Diana Wu, Shreya Menon, Shushan Toneyan, Kerstin Seidel, Liang Wang, Jenille Tan, Shang-Yang Chen, Timothy Keyes, Aleksander Chlebowski, Yu Guo, Ciara Metcalfe, Marc Hafner, Christian W. Siebel, M. Ryan Corces, Robert Yauch, Shiqi Xie, Xiaosai Yao. 2023. "Inference of single-cell transcription factor activity to dissect mechanisms of lineage plasticity and drug response" bioRxiv 2023.11.27.568955; doi: []( Contact: [Xiaosai Yao](, Genentech Inc.