HiCociety: Inferring Chromatin Interaction Modules from 3C-Based Data
Identifies chromatin interaction modules by constructing a Hi-C contact network based on statistically significant interactions, followed by network clustering. The method enables comparison of module connectivity across two Hi-C datasets and is capable of detecting cell-type-specific regulatory modules. By integrating network analysis with chromatin conformation data, this approach provides insights into the spatial organization of the genome and its functional implications in gene regulation. Author: Sora Yoon (2025) <https://github.com/ysora/HiCociety>.
Version:
0.1.38
Depends:
R (≥ 3.5.0)
Imports:
strawr,
shape,
fitdistrplus,
igraph,
ggraph,
foreach,
doParallel,
biomaRt,
TxDb.Hsapiens.UCSC.hg38.knownGene,
TxDb.Mmusculus.UCSC.mm10.knownGene,
org.Mm.eg.db,
org.Hs.eg.db,
Rcpp,
AnnotationDbi,
GenomicFeatures, parallel,
IRanges,
S4Vectors, grDevices, graphics, stats,
BiocManager,
BiocGenerics,
GenomicRanges,
pracma,
signal,
HiCocietyExample
Published:
2025年05月13日
Author:
Sora Yoon [aut, cre]
Maintainer:
Sora Yoon <sora.yoon at pennmedicine.upenn.edu>
NeedsCompilation:
yes
Documentation:
Downloads:
macOS binaries:
r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available
Linking:
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https://CRAN.R-project.org/package=HiCociety
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