HiCPotts
This is the development version of HiCPotts; for the stable release version, see HiCPotts.
Hierarchical Modeling to Identify and Correct Genomic Biases in Hi-C
Bioconductor version: Development (3.24)
Bayesian analysis of Hi-C interaction counts using a three-state hierarchical mixture model with Potts spatial dependence and genomic distance, GC-content, transposable-element and accessibility covariates. The three biological components are low-mean noise, true signal with a distinct covariate-response pattern, and elevated false signal whose covariate-response slopes resemble the noise component. Robust regression fitting uses a multi-chain soft empirical-Bayes pilot to construct one shared prior that is frozen for all production chains, dispersion uses component-group-specific Gamma priors, zero inflation uses a conjugate augmented Gibbs step, and spatial coupling uses retained-state approximate Bayesian computation. The official classification pools post-burn-in latent-state frequencies from the fitted model; parameter-plus-Potts allocation is retained as a separate sensitivity analysis. Parameter summaries include posterior intervals, effective sample sizes and split-chain R-hat, with configurable diagnostic criteria for reporting. Cached native likelihood calculations, direct checkerboard allocation, reproducible cross-platform parallel chains, fit provenance and stage timings improve computational efficiency and auditability without changing the model target or official classification rule.
Author: Itunu. Godwin Osuntoki [aut, cre]
, Nicolae. Radu Zabet [aut]
Maintainer: Itunu. Godwin Osuntoki <hitunes4 at gmail.com>
citation("HiCPotts")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
## The following initializes the development version of Bioconductor
BiocManager::install(version = "devel")
BiocManager::install("HiCPotts")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("HiCPotts")| Bayesian Analysis of Hi-C Interactions with HiCPotts | HTML | R Script |
| HiCPotts Function and Argument Reference | HTML | R Script |
| Reference Manual | ||
| NEWS | Text | |
| LICENSE | Text |
Details
| biocViews | Bayesian, Classification, DataImport, FunctionalGenomics, GenomeAnnotation, GenomeWideAssociation, HiddenMarkovModel, PeakDetection, Regression, Software, Spatial, StatisticalMethod |
| Version | 1.3.1 |
| In Bioconductor since | BioC 3.22 (R-4.5) (1 year) |
| License | GPL-3 | file LICENSE |
| Depends | R (>= 4.5) |
| Imports | Rcpp (>= 0.11.0), Biostrings, GenomicRanges, IRanges, S4Vectors, ggnewscale, parallel, rhdf5, rlang, rtracklayer, stats, withr |
| System Requirements | |
| URL | https://github.com/igosungithub/HiCPotts |
| Bug Reports | https://github.com/igosungithub/HiCPotts/issues |
See More
| Suggests | BSgenome, BSgenome.Dmelanogaster.UCSC.dm6, BiocManager, BiocStyle, ggplot2 (>= 3.5.0), knitr (>= 1.30), reshape2 (>= 1.4.4), rmarkdown (>= 2.10), testthat (>= 3.0.0) |
| Linking To | Rcpp, RcppArmadillo |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | HiCPotts_1.3.1.tar.gz |
| Windows Binary (x86_64) | HiCPotts_1.3.0.zip |
| macOS Binary (big-sur-x86_64) | HiCPotts_1.3.1.tgz |
| macOS Binary (sonoma-arm64) | HiCPotts_1.3.1.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/HiCPotts |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/HiCPotts |
| Bioc Package Browser | https://code.bioconductor.org/browse/HiCPotts/ |
| Package Short Url | https://bioconductor.org/packages/HiCPotts/ |
| Package Downloads Report | Download Stats |