transformGamPoi
Bioc currentVariance Stabilizing Transformation for Gamma-Poisson Models
Release Lineage
Entered 3.14 · Oct 27, 2021
Current · Requires R 4.6
Description
Variance-stabilizing transformations help with the analysis of heteroskedastic data (i.e., data where the variance is not constant, like count data). This package provide two types of variance stabilizing transformations: (1) methods based on the delta method (e.g., 'acosh', 'log(x+1)'), (2) model residual based (Pearson and randomized quantile residuals).
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
23 4 exported
Complexity
5.5 avg / 20 max
Call network
23 nodes / 31 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
1,825
Files
32
Compiled share
2.9%
Has compiled src
Yes
Language breakdown
API
Exported functions
4
Internal functions
16
Testing & CI
Has tests
Yes
Test-to-code ratio
0.44
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
–
Unsafe pattern score
0
Dep constraint coverage
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
–
System requirements
–
C++ standard
–
License
GPL-3
License flags
SPDX valid, OSI approved
History
Versions
10
First release
2021-10-26
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
–
Dep drift
1
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
- 88%
- Return-value docs
- 100%
- References docs
- 60%
Topics
Depended on by (1)
Bioconductor (1)
People
- Constantin Ahlmann-Eltze author maintainer
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("transformGamPoi")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 v2026-08-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.