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 |
| 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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