CeTF
Bioc currentCoexpression for Transcription Factors using Regulatory Impact Factors and Partial Correlation and Information Theory analysis
Release Lineage
Entered 3.11 · Apr 28, 2020
Current · Requires R 4.6
Description
This package provides the necessary functions for performing the Partial Correlation coefficient with Information Theory (PCIT) (Reverter and Chan 2008) and Regulatory Impact Factors (RIF) (Reverter et al. 2010) algorithm. The PCIT algorithm identifies meaningful correlations to define edges in a weighted network and can be applied to any correlation-based network including but not limited to gene co-expression networks, while the RIF algorithm identify critical Transcription Factors (TF) from gene expression data. These two algorithms when combined provide a very relevant layer of information for gene expression studies (Microarray, RNA-seq and single-cell RNA-seq data).
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
30 24 exported
Complexity
5.9 avg / 25 max
Call network
30 nodes / 12 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
5,462
Files
108
Compiled share
3.1%
Has compiled src
Yes
Language breakdown
API
Exported functions
24
Internal functions
1
Testing
Has tests
Yes
Test-to-code ratio
0.13
testthat edition
–
Docs
Roxygen coverage
95.8%
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
System requirements
7 externallibcurl4-openssl-dev, libxml2-dev, libssl-dev, gfortran, build-essential, libz-dev, zlib1g-dev
C++ standard
–
License
GPL-3
License flags
SPDX valid, OSI approved
History
Versions
13
First release
2020-08-27
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
- 36
- Examples that run
- 85%29 run in a plain check · 5 never run
- Exported functions with examples
- 96%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 19%
Repository practices
Checks read the Bioconductor git repository (git.bioconductor.org), branch RELEASE_3_23.
No development-tooling practices detected in the Bioconductor git repository.
Datasets
Topics
People
- Carlos Alberto Oliveira de Biagi Junior author maintainer
- Wilson Araújo da Silva Junior author thesis advisor
- João Paulo Bianchi Ximenez contributor
- Marcelo Gomes de Paula contributor
- Breno Osvaldo Funicheli author
- Ricardo Perecin Nociti author
- Patrícia de Cássia Ruy contributor
- Rafael dos Santos Bezerra contributor
Cite
Cite this package
Run in R for the authors' entry:
citation("CeTF")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1186/s12864-021-07918-2.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-19, which the citation names so these numbers can be found later. More on citing and the projects behind them.