Contains flexible and user-friendly functions to find, import, and harmonise epigenomic peaks data from GEO, ENCODE, ROADMAP, and AnnotationHub. Efficiently imports multiple peak files in one function call (either genome-wide or specific regions) using parallelisation. When peaks are not available, automatically calls peaks from bedGraph or bigWig files.
- Multi-source import: Fetch peaks from GEO, ENCODE, ROADMAP, and AnnotationHub with a single function
- Automatic peak calling: When peak files aren’t available, automatically calls peaks from bedGraph or bigWig files using MACS3 or SEACR
- Region filtering: Import only peaks overlapping regions of interest
- Genome build handling: Automatic liftOver between genome builds (hg19/hg38)
- Parallelisation: Efficiently import multiple peak files in parallel
if(!require("BiocManager")) install.packages("BiocManager")
BiocManager::install("neurogenomics/PeakyFinders")
library(PeakyFinders)library(PeakyFinders)
# Import peaks from multiple sources at once
ids <- c(
"GSM945244", # GEO
"ENCSR000AHD", # ENCODE
"AH32001" # AnnotationHub
)
peaks <- import_peaks(
ids = ids,
builds = "hg38",
searches = list(narrowPeak = "narrowpeak")
)
# Filter to a specific region
query_region <- GenomicRanges::GRanges("chr22:1-50000000")
peaks_filtered <- import_peaks(
ids = ids,
builds = "hg38",
query_granges = query_region,
query_granges_build = "hg38"
)
# Search for available datasets
encode_metadata <- search_encode(
target = "H3K27ac",
biosample = "K562"
)If you use PeakyFinders, please cite:
Brian M. Schilder, Nathan G. Skene (2024). PeakyFinders: Mining, Calling, and Importing Epigenomic Peaks in R. R package version 0.99.4
UK Dementia Research Institute Department of Brain Sciences Faculty of Medicine Imperial College London GitHub DockerHub