epiregulon
Gene regulatory network inference from single cell epigenomic data
Bioconductor version: 3.23 · Package version: 2.2.0
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("epiregulon") Details
| Maintainer | Xiaosai Yao <xiaosai.yao@gmail.com> |
| Author | Xiaosai Yao [aut, cre] (ORCID: <https://orcid.org/0000-0001-9729-0726>), Tomasz Włodarczyk [aut] (ORCID: <https://orcid.org/0000-0003-1554-9699>), Aaron Lun [aut], Shang-Yang Chen [aut] |
| License | MIT + file LICENSE |
| URL | https://github.com/xiaosaiyao/epiregulon/ |
| Bug Reports | https://github.com/xiaosaiyao/epiregulon/issues |
| Downloads rank | 194 |
| Source branch | RELEASE_3_23 |
| biocViews | GeneExpression, GeneRegulation, GeneTarget, Network, NetworkInference, SingleCell, Software, Transcription |
Documentation
Download
Dependencies
Depends: R (>= 4.5.0), SingleCellExperiment
Imports: AnnotationHub, BiocParallel, ExperimentHub, Matrix, Rcpp, S4Vectors, SummarizedExperiment, checkmate, entropy, lifecycle, methods, scran, scuttle, stats, utils, AnnotationHub, GenomeInfoDb, GenomicRanges, BSgenome.Hsapiens.UCSC.hg19, BSgenome.Hsapiens.UCSC.hg38, BSgenome.Mmusculus.UCSC.mm10, motifmatchr, IRanges, scrapper
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, parallel, BiocStyle, testthat (>= 3.0.0), coin, scater, scMultiome
Reverse dependencies
Suggests Me (1): epiregulon.extra