REMP
Bioc currentRepetitive Element Methylation Prediction
Release Lineage
Entered 3.5 · Apr 25, 2017
Current · Requires R 4.6
Description
Machine learning-based tools to predict DNA methylation of locus-specific repetitive elements (RE) by learning surrounding genetic and epigenetic information. These tools provide genomewide and single-base resolution of DNA methylation prediction on RE that are difficult to measure using array-based or sequencing-based platforms, which enables epigenome-wide association study (EWAS) and differentially methylated region (DMR) analysis on RE.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
67 13 exported
Complexity
4.6 avg / 40 max
Call network
67 nodes / 93 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
5,688
Files
45
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
13
Internal functions
53
Recent export changes
Testing & CI
Has tests
No
Test-to-code ratio
0.00
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
3
Dep constraint coverage
7.4%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
3.6
System requirements
–
C++ standard
–
License
GPL-3
License flags
SPDX valid, OSI approved
History
Versions
19
First release
2017-09-25
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
–
Dep drift
8
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 6%
Topics
People
- Yinan Zheng author maintainer
- Lifang Hou author cph
- Warren Kibbe author
- Lei Liu author
- Wei Zhang author
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("REMP")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.
From data release v2026-08-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.