This is the development version of epiregulon; for the stable release version, see epiregulon.
Gene regulatory network inference from single cell epigenomic dataBioconductor version: Development (3.22)
Gene regulatory networks model the underlying gene regulation hierarchies that drive gene expression and observed phenotypes. Epiregulon infers TF activity in single cells by constructing a gene regulatory network (regulons). This is achieved through integration of scATAC-seq and scRNA-seq data and incorporation of public bulk TF ChIP-seq data. Links between regulatory elements and their target genes are established by computing correlations between chromatin accessibility and gene expressions.
Author: Xiaosai Yao [aut, cre] ORCID: 0000-0001-9729-0726 , Tomasz WÅodarczyk [aut] ORCID: 0000-0003-1554-9699 , Aaron Lun [aut], Shang-Yang Chen [aut]
Maintainer: Xiaosai Yao <xiaosai.yao at gmail.com>
Citation (from within R, entercitation("epiregulon")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("epiregulon")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("epiregulon")Follow Installation instructions to use this package in your R session.
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