An R package designed to integrate and visualize various levels of epigenomic information, including but not limited to: ChIP, Histone, ATAC, and RNA sequencing. epiRomics is also designed for regulatory network analysis in order to identify enhancer and enhanceosome regions from these data.
Please contact ammawla@ucdavis.edu for suggestions, feedback, or bug reporting.
Explore epiRomics results interactively through our companion Shiny web applications:
Shiny epiRomics Mouse Islet Enhanceosome Browser — Interactive browser exploring mouse pancreatic islet enhancers and enhanceosome analysis results from our 2023 BMC Genomics publication.
Paper: Alex M. Mawla, Talitha van der Meulen, Mark O. Huising. (2023). Chromatin accessibility differences between alpha, beta, and delta cells identifies common and cell type-specific enhancers. BMC Genomics. 10.1186/s12864-023-09293-6
Shiny epiRomics Human Islet Enhanceosome Browser — Interactive browser exploring human pancreatic islet enhancer and enhanceosome analysis results used to create the example data and vignette for the epiRomics Package.
Package: Alex M. Mawla & Mark O. Huising. (2021). epiRomics: a multi-omics R package to identify and visualize enhancers. bioRxiv 2021.08.19.456732. 10.1101/2021.08.19.456732
- Multi-omics Integration: Seamlessly integrate ChIP-seq, ATAC-seq, RNA-seq, and histone modification data
- Enhancer Identification: Identify putative enhancer regions using histone mark combinations
- Enhanceosome Analysis: Detect enhanceosome regions through co-transcription factor analysis
- Memory-Efficient Processing: Built-in BigWig caching for large-scale data analysis
- Comprehensive Visualization: Generate publication-ready genomic tracks and plots
- Robust Error Handling: Comprehensive parameter validation and error messages
epiRomics requires R version 4.5.0 or higher and several Bioconductor packages. Make sure you have the latest version of R and Bioconductor installed.
if (!requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}
BiocManager::install("epiRomics")
library(epiRomics)
# Optional: download the full example dataset (~1.3 GB, one-time,
# cached via BiocFileCache). The package also ships a small toy
# subset in `inst/extdata/toy/` that runs all examples without any
# download.
epiRomics::cache_data()Note: The Bioconductor release channel is the supported install path. GitHub installation is intended for developers tracking the
mainbranch between releases and is not advised for regular users.
if (!requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}
BiocManager::install("Huising-Lab/epiRomics")# Load the package
library(epiRomics)
# Build epiRomics database
database <- build_database(
db_file = "path/to/your/data.csv",
txdb_organism = "TxDb.Hsapiens.UCSC.hg38.knownGene",
genome = "hg38",
organism = "org.Hs.eg.db"
)
# Identify putative enhancers
enhancers <- find_enhancers_by_comarks(
database = database,
histone_mark_1 = "h3k4me1",
histone_mark_2 = "h3k27ac"
)
# Identify enhanceosomes
enhanceosomes <- find_enhanceosomes(
putative_enhancers = enhancers,
database = database
)
# Visualize results
plot_tracks(
enhanceosomes,
index = 1,
database = database,
track_connection = your_track_data
)- pkgdown site (live): https://huising-lab.github.io/epiRomics/ — full reference manual, both vignettes, and changelog rendered as a browsable website. This is the best entry point while the Bioconductor landing page is still pending.
- Bioconductor landing page: https://bioconductor.org/packages/epiRomics/ (available after the package is accepted into a Bioconductor release).
- Vignettes (after install):
browseVignettes("epiRomics")- Getting Started with epiRomics — lightweight walkthrough using the bundled toy dataset
- Full Analysis with epiRomics — complete human pancreatic islet analysis (uses
cache_data())
- Reference manual (after install):
help(package = "epiRomics", help_type = "html")
Example data is downloaded on demand via cache_data() (~1.3 GB, cached locally after first download). The dataset focuses on delineating putative human pancreatic islet enhancers between alpha and beta cells and includes:
- Human pancreatic islet alpha and beta ATAC-seq data from GEO accession GSE76268
- ChIP-seq data for transcription factors Foxa2, MafB, Nkx2.2, Nkx6.1, and Pdx1
- Histone modification data (H3K27ac, H3K4me1,H3K27me3, H3K9me3, H3K4me3, H3K36me3, H2A.Z)
- FANTOM5 human enhancer database
- Human ultra-conserved non-coding elements (UCNEs)
If you use epiRomics, please cite:
Alex M. Mawla, Talitha van der Meulen, Mark O. Huising. (2023). Chromatin accessibility differences between alpha, beta, and delta cells identifies common and cell type-specific enhancers. BMC Genomics. 10.1186/s12864-023-09293-6
Alex M. Mawla & Mark O. Huising. (2021). epiRomics: a multi-omics R package to identify and visualize enhancers. bioRxiv 2021.08.19.456732. 10.1101/2021.08.19.456732
We welcome contributions! Please feel free to submit issues, feature requests, or pull requests on our GitHub repository.
This package is licensed under the Artistic License 2.0. See the LICENSE file for details.
For questions, suggestions, or bug reports, please contact:
- Maintainer: Alex M. Mawla ammawla@ucdavis.edu
- GitHub Issues: https://github.com/Huising-Lab/epiRomics/issues
Problem: Package dependencies fail to install
Solution: Make sure you have the latest version of R (≥ 4.5.0) and Bioconductor:
# Update R packages
update.packages(ask = FALSE)
# Update Bioconductor
BiocManager::install(version = BiocManager::version())
# If installation fails, try installing core dependencies manually:
BiocManager::install(c("AnnotationDbi", "annotatr", "BiocGenerics",
"GenomeInfoDb", "GenomicFeatures", "GenomicRanges",
"IRanges", "org.Hs.eg.db", "rtracklayer",
"TxDb.Hsapiens.UCSC.hg38.knownGene", "data.table"))Problem: Compilation errors on Linux
Solution: Install required system dependencies:
# Ubuntu/Debian
sudo apt-get update
sudo apt-get install -y libxml2-dev libcurl4-openssl-dev libssl-dev
# CentOS/RHEL
sudo yum install libxml2-devel openssl-devel libcurl-devel
