NBAMSeq
Bioc currentNegative Binomial Additive Model for RNA-Seq Data
Release Lineage
Entered 3.9 · May 3, 2019
Current · Requires R 4.6
Description
High-throughput sequencing experiments followed by differential expression analysis is a widely used approach to detect genomic biomarkers. A fundamental step in differential expression analysis is to model the association between gene counts and covariates of interest. NBAMSeq a flexible statistical model based on the generalized additive model and allows for information sharing across genes in variance estimation.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
7 5 exported
Complexity
7.3 avg / 17 max
Call network
7 nodes / 3 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
2,126
Files
23
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
8
Internal functions
2
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.33
testthat edition
–
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
12.5%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
3.6
System requirements
–
C++ standard
–
License
GPL-2
License flags
SPDX valid, OSI approved
History
Versions
15
First release
2019-08-16
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
–
Dep drift
0
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
- 100%
- Return-value docs
- 100%
- References docs
- 71%
Topics
Depended on by (1)
Bioconductor (1)
People
- Xu Ren author maintainer
- Pei Fen Kuan author
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("NBAMSeq")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 v2026-08-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.