iasva
Bioc currentIteratively Adjusted Surrogate Variable Analysis
Release Lineage
Entered 3.8 · Oct 31, 2018
Current · Requires R 4.6
Description
Iteratively Adjusted Surrogate Variable Analysis (IA-SVA) is a statistical framework to uncover hidden sources of variation even when these sources are correlated. IA-SVA provides a flexible methodology to i) identify a hidden factor for unwanted heterogeneity while adjusting for all known factors; ii) test the significance of the putative hidden factor for explaining the unmodeled variation in the data; and iii), if significant, use the estimated factor as an additional known factor in the next iteration to uncover further hidden factors.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
8 4 exported
Complexity
6.1 avg / 17 max
Call network
8 nodes / 5 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
1,050
Files
21
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
4
Internal functions
3
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.27
testthat edition
–
CI present
No
CI type
[]
PR gated
No
Docs
Roxygen coverage
100%
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
3.5
System requirements
–
C++ standard
–
License
GPL-2
License flags
SPDX valid, OSI approved
History
Versions
16
First release
2019-01-04
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
- 0%
Topics
People
- Donghyung Lee author maintainer
- Anthony Cheng author
- Nathan Lawlor author
- Duygu Ucar author
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("iasva")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 v2026-08-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.