Package: HiSpaR
Type: Package
Title: Hierarchical Inference of Spatial Positions from Hi-C Data
Version: 1.0.0
Date: 2026-01-15
Authors@R: c(
    person("Yingcheng", "Luo", email = "lyc22@mails.tsinghua.edu.cn", role = c("aut", "cre"))
    )
Description: Provides R bindings for HiSpa, a hierarchical Bayesian
        model for inferring three-dimensional chromatin structures from
        Hi-C contact matrices using Markov Chain Monte Carlo (MCMC)
        sampling. The package implements a cluster-based hierarchical
        approach that efficiently handles large-scale Hi-C datasets. It
        uses Rcpp and RcppArmadillo for efficient C++ integration with
        the original HiSpa C++ implementation, enabling fast
        computation of chromatin structure inference through parallel
        MCMC sampling.
License: MIT + file LICENSE
Depends: R (>= 4.5.0)
Imports: Rcpp (>= 1.0.0), utils, stats, Matrix, HiCExperiment
biocViews: Software, Epigenetics, HiC, StructuralPrediction, Bayesian,
        Spatial
LinkingTo: Rcpp, RcppArmadillo
SystemRequirements: C++17, GNU make, Armadillo (>= 9.0), OpenMP
URL: https://github.com/masterStormtrooper/HiSpaR
BugReports: https://github.com/masterStormtrooper/HiSpaR/issues
Encoding: UTF-8
LazyData: false
RoxygenNote: 7.3.3
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, BiocStyle, rgl,
        HiContactsData, HiContacts, plotly, callr
VignetteBuilder: knitr
Config/pak/sysreqs: make libssl-dev zlib1g-dev
Repository: https://bioc-release.r-universe.dev
Date/Publication: 2026-04-28 13:06:36 UTC
RemoteUrl: https://github.com/bioc/HiSpaR
RemoteRef: RELEASE_3_23
RemoteSha: 4faeb40b8aba7be85abf7d55801eafe08af3397b
NeedsCompilation: yes
Packaged: 2026-04-29 22:21:23 UTC; root
Author: Yingcheng Luo [aut, cre]
Maintainer: Yingcheng Luo <lyc22@mails.tsinghua.edu.cn>
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-29 22:58:14 UTC; unix
