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.
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
3,425
Files
61
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
7
Internal functions
5
Testing & CI
Has tests
Yes
Test-to-code ratio
0.15
testthat edition
–
CI present
Yes
CI type
["github-actions","travis"]
PR gated
Yes
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
- Examples that run
- 100%
- Documented parameters
- 90%
- Return-value docs
- 100%
- References docs
- 0%
Topics
Depended on by (1)
Bioconductor (1)
People
- Mikhail Dozmorov author maintainer
- Spiro Stilianoudakis author
Cite
Cite this package
Run in R for the authors' preferred citation:
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Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
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