RegParallel
Bioc currentStandard regression functions in R enabled for parallel processing over large data-frames
Release Lineage
Entered 3.8 · Oct 31, 2018
Current · Requires R 4.6
Description
In many analyses, a large amount of variables have to be tested independently against the trait/endpoint of interest, and also adjusted for covariates and confounding factors at the same time. The major bottleneck in these is the amount of time that it takes to complete these analyses. With RegParallel, a large number of tests can be performed simultaneously. On a 12-core system, 144 variables can be tested simultaneously, with 1000s of variables processed in a matter of seconds via 'nested' parallel processing. Works for logistic regression, linear regression, conditional logistic regression, Cox proportional hazards and survival models, and Bayesian logistic regression. Also caters for generalised linear models that utilise survey weights created by the 'survey' CRAN package and that utilise 'survey::svyglm'.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
7 0 exported
Complexity
26.3 avg / 35 max
Call network
7 nodes / 6 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
4,145
Files
28
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
7
Internal functions
7
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.00
testthat edition
–
CI present
No
CI type
[]
PR gated
No
Docs
Roxygen coverage
0%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
100%
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
16
First release
2018-10-30
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
100%
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
- not tracked
- Documented parameters
- not tracked
- Return-value docs
- not tracked
- References docs
- not tracked
Topics
People
- Kevin Blighe author maintainer
- Sarega Gurudas contributor
- Jessica Lasky-Su author