qusage
Bioc currentqusage: Quantitative Set Analysis for Gene Expression
Release Lineage
Entered 2.13 · Oct 15, 2013
Current · Requires R 4.6
Description
This package is an implementation the Quantitative Set Analysis for Gene Expression (QuSAGE) method described in (Yaari G. et al, Nucl Acids Res, 2013). This is a novel Gene Set Enrichment-type test, which is designed to provide a faster, more accurate, and easier to understand test for gene expression studies. qusage accounts for inter-gene correlations using the Variance Inflation Factor technique proposed by Wu et al. (Nucleic Acids Res, 2012). In addition, rather than simply evaluating the deviation from a null hypothesis with a single number (a P value), qusage quantifies gene set activity with a complete probability density function (PDF). From this PDF, P values and confidence intervals can be easily extracted. Preserving the PDF also allows for post-hoc analysis (e.g., pair-wise comparisons of gene set activity) while maintaining statistical traceability. Finally, while qusage is compatible with individual gene statistics from existing methods (e.g., LIMMA), a Welch-based method is implemented that is shown to improve specificity. The QuSAGE package also includes a mixed effects model implementation, as described in (Turner JA et al, BMC Bioinformatics, 2015), and a meta-analysis framework as described in (Meng H, et al. PLoS Comput Biol. 2019). For questions, contact Chris Bolen (cbolen1@gmail.com) or Steven Kleinstein (steven.kleinstein@yale.edu)
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
36 20 exported
Complexity
9.7 avg / 44 max
Call network
36 nodes / 46 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
4,604
Files
34
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
22
Internal functions
16
Testing & CI
Has tests
No
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
0%
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
GPL (>= 2)
License flags
SPDX valid, OSI approved
History
Versions
26
First release
2013-11-21
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
–
Dep drift
5
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
- 79%
- Return-value docs
- 67%
- References docs
- 14%
Topics
Depended on by (2)
Bioconductor (1)
CRAN (1)
People
- Christopher Bolen Developer author maintainer
- Derek Blankenship Developer author
- Gur Yaari Developer author
- Hailong Meng Developer author
- Jacob Turner Developer author
- Juilee Thakar Developer author
- Steven Kleinstein Developer author
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("qusage")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.