knowYourCG
Bioc currentFunctional analysis of DNA methylome datasets
Release Lineage
Entered 3.19 · May 1, 2024
Current · Requires R 4.6
Description
KnowYourCG (KYCG) is a supervised learning framework designed for the functional analysis of DNA methylation data. Unlike existing tools that focus on genes or genomic intervals, KnowYourCG directly targets CpG dinucleotides, featuring automated supervised screenings of diverse biological and technical influences, including sequence motifs, transcription factor binding, histone modifications, replication timing, cell-type-specific methylation, and trait-epigenome associations. KnowYourCG addresses the challenges of data sparsity in various methylation datasets, including low-pass Nanopore sequencing, single-cell DNA methylomes, 5-hydroxymethylation profiles, spatial DNA methylation maps, and array-based datasets for epigenome-wide association studies and epigenetic clocks (<doi:10.1126/sciadv.adw3027>).
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
249 25 exported
Complexity
4 avg / 18 max
Call network
249 nodes / 311 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
10,490
Files
110
Compiled share
59.6%
Has compiled src
Yes
Language breakdown
API
Exported functions
25
Internal functions
30
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.01
testthat edition
3
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
4.4.0
System requirements
–
C++ standard
–
License
AGPL-3
License flags
SPDX valid, OSI approved
History
Versions
5
First release
2024-04-30
Latest release
2026-04-28
Avg cadence
178 days
Cold removal rate
100%
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
- 97%
- Return-value docs
- 100%
- References docs
- 0%
Topics
People
- David Goldberg author maintainer
- Hongxiang Fu contributor
- Wanding Zhou author fnd