Inferring Chromatin Interaction Modules from 3C-Based Data R package HiCociety version 0.1.39 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>. Software Depends: R (>= 3.5.0) Imports: strawr, shape, fitdistrplus, igraph, foreach, doParallel, Rcpp, AnnotationDbi, GenomicFeatures, parallel, IRanges, S4Vectors, grDevices, graphics, stats, GenomicRanges, pracma, signal, HiCocietyExample LinkingTo: Rcpp Suggests: knitr, rmarkdown, testthat (>= 3.0.0), BiocManager, biomaRt, TxDb.Hsapiens.UCSC.hg38.knownGene, TxDb.Mmusculus.UCSC.mm10.knownGene, org.Mm.eg.db, org.Hs.eg.db Sora Yoon <ysora90@gmail.com> Comprehensive R Archive Network (CRAN) Sora Yoon [aut, cre] GPL-3 2026-02-16 application/tgz https://CRAN.R-project.org/package=HiCociety doi:10.32614/CRAN.package.HiCociety