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 |
| LinkingTo: | Rcpp |
| Published: | 2025-05-13 |
| DOI: | 10.32614/CRAN.package.HiCociety |
| Author: | Sora Yoon [aut, cre] |
| Maintainer: | Sora Yoon <sora.yoon at pennmedicine.upenn.edu> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| CRAN checks: | HiCociety results |
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