preciseTAD
Bioc currentpreciseTAD: A machine learning framework for precise TAD boundary prediction
Release Lineage
Entered 3.12 · Oct 28, 2020
Current · Requires R 4.6
Description
preciseTAD provides functions to predict the location of boundaries of topologically associated domains (TADs) and chromatin loops at base-level resolution. As an input, it takes BED-formatted genomic coordinates of domain boundaries detected from low-resolution Hi-C data, and coordinates of high-resolution genomic annotations from ENCODE or other consortia. preciseTAD employs several feature engineering strategies and resampling techniques to address class imbalance, and trains an optimized random forest model for predicting low-resolution domain boundaries. Translated on a base-level, preciseTAD predicts the probability for each base to be a boundary. Density-based clustering and scalable partitioning techniques are used to detect precise boundary regions and summit points. Compared with low-resolution boundaries, preciseTAD boundaries are highly enriched for CTCF, RAD21, SMC3, and ZNF143 signal and more conserved across cell lines. The pre-trained model can accurately predict boundaries in another cell line using CTCF, RAD21, SMC3, and ZNF143 annotation data for this cell line.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
12 7 exported
Complexity
9.6 avg / 51 max
Call network
12 nodes / 9 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
3,280
Files
51
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
7
Internal functions
5
Testing
Has tests
Yes
Test-to-code ratio
0.15
testthat edition
–
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
0
Dep constraint coverage
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.1
System requirements
–
C++ standard
–
License
MIT + file LICENSE
License flags
SPDX valid, OSI approved
History
Versions
12
First release
2020-10-27
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
- Help pages
- 14
- Examples that run
- 100%6 run in a plain check
- Exported functions with examples
- 86%
- Documented parameters
- 90%
- Return-value docs
- 100%
- Help pages citing references
- 0%
- preciseTAD HTML
Repository practices
9 development-tooling and community-health practices detected across 4 families in the upstream repository
Checks run against github.com/dozmorovlab/precisetad on 2026-10-25.
The R CMD check workflow runs on Linux, macOS and Windows
GitHub Pages site last deployed 2022-04-22 · The repository has a site deploy workflow
Datasets
| Name | Class | Size | Also in |
|---|---|---|---|
| arrowhead_gm12878_5kb | data.frame | 8,409 × 3 | No other package |
| tfbsList | – | – | – |
Topics
Suggested by (1)
People
- Mikhail Dozmorov author maintainer
- Spiro Stilianoudakis author
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("preciseTAD")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
The repository also keeps a CITATION.cff.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.