hicream: HIC diffeREntial Analysis Method (original) (raw)
Perform Hi-C data differential analysis based on pixel-level differential analysis and a post hoc inference strategy to quantify signal in clusters of pixels. Clusters of pixels are obtained through a connectivity-constrained two-dimensional hierarchical clustering.
Version:
0.0.2
Depends:
R (≥ 4.0.0), reticulate
Imports:
adjclust, auk, BiocGenerics, csaw, diffHic, dplyr, edgeR, GenomeInfoDb, GenomicRanges, InteractionSet, limma, Matrix, methods, reshape2, rlang, S4Vectors, stats, SummarizedExperiment, utils, viridis
Suggests:
Published:
2025-11-19
DOI:
Author:
Elise Jorge [aut, cre], Sylvain Foissac 
[aut], Toby Hocking [aut], Pierre Neuvial [aut], Nathalie Vialaneix [aut], Gilles Blanchard [ctb], Guillermo Durand [ctb], Nicolas Enjalbert-Courrech [ctb], Etienne Roquain [ctb]
Maintainer:
Elise Jorge <elise.jorge at inrae.fr>
BugReports:
https://forge.inrae.fr/scales/hicream/-/issues
License:
URL:
https://forge.inrae.fr/scales/hicream
NeedsCompilation:
no
SystemRequirements:
Python (>= 3.9)
Materials:
CRAN checks: