cpvSNP
Bioc currentGene set analysis methods for SNP association p-values that lie in genes in given gene sets
Release Lineage
Entered 3.1 · Apr 17, 2015
Current · Requires R 4.6
Description
Gene set analysis methods exist to combine SNP-level association p-values into gene sets, calculating a single association p-value for each gene set. This package implements two such methods that require only the calculated SNP p-values, the gene set(s) of interest, and a correlation matrix (if desired). One method (GLOSSI) requires independent SNPs and the other (VEGAS) can take into account correlation (LD) among the SNPs. Built-in plotting functions are available to help users visualize results.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
10 9 exported
Complexity
5.8 avg / 14 max
Call network
10 nodes / 4 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
2,254
Files
50
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
9
Internal functions
1
Testing & CI
Has tests
Yes
Test-to-code ratio
0.00
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
14.3%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
2.10
System requirements
–
C++ standard
–
License
Artistic-2.0
License flags
SPDX valid, OSI approved
History
Versions
23
First release
2015-04-16
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
- 69%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 8%
Topics
People
Caitlin McHugh
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("cpvSNP")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.