multiHiCcompare
Bioc currentNormalize and detect differences between Hi-C datasets when replicates of each experimental condition are available
Release Lineage
Entered 3.8 · Oct 31, 2018
Current · Requires R 4.6
Description
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.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
31 16 exported
Complexity
6 avg / 24 max
Call network
31 nodes / 16 edges
Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
Code
Structure
Lines of code
4,264
Files
81
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
16
Internal functions
15
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.04
testthat edition
–
CI present
No
CI type
[]
PR gated
No
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
0%
Unsafe pattern score
0
Dep constraint coverage
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.0.0
System requirements
–
C++ standard
–
License
MIT + file LICENSE
License flags
SPDX valid, OSI approved
History
Versions
16
First release
2018-10-30
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
–
Dep drift
3
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Examples that run
- 86%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Topics
Depended on by (3)
Bioconductor (3)
People
- Mikhail Dozmorov author maintainer
- John Stansfield author
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("multiHiCcompare")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
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