multiHiCcompare
Normalize and detect differences between Hi-C datasets when replicates of each experimental condition are available
Bioconductor version: 3.23 · Package version: 1.30.0
multiHiCcompare provides functions for joint normalization and difference detection in multiple Hi-C datasets. This extension of the original HiCcompare package now allows for Hi-C experiments with more than 2 groups and multiple samples per group. multiHiCcompare operates on processed Hi-C data in the form of sparse upper triangular matrices. It accepts four column (chromosome, region1, region2, IF) tab-separated text files storing chromatin interaction matrices. multiHiCcompare provides cyclic loess and fast loess (fastlo) methods adapted to jointly normalizing Hi-C data. Additionally, it provides a general linear model (GLM) framework adapting the edgeR package to detect differences in Hi-C data in a distance dependent manner.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("multiHiCcompare") Details
| Maintainer | Mikhail Dozmorov <mikhail.dozmorov@gmail.com> |
| Author | Mikhail Dozmorov [aut, cre] (ORCID: <https://orcid.org/0000-0002-0086-8358>), John Stansfield [aut] |
| License | MIT + file LICENSE |
| URL | https://github.com/dozmorovlab/multiHiCcompare |
| Bug Reports | https://github.com/dozmorovlab/multiHiCcompare/issues |
| Downloads rank | 401 |
| Source branch | RELEASE_3_23 |
| biocViews | HiC, Normalization, Sequencing, Software |
Documentation
Download
Dependencies
Depends: R (>= 4.0.0)
Imports: data.table, dplyr, HiCcompare, edgeR, BiocParallel, qqman, pheatmap, methods, GenomicRanges, graphics, stats, utils, pbapply, GenomeInfoDbData, GenomeInfoDb, aggregation