BioQC
Bioc currentDetect tissue heterogeneity in expression profiles with gene sets
Release Lineage
Entered 3.3 · May 4, 2016
Current · Requires R 4.6
Description
BioQC performs quality control of high-throughput expression data based on tissue gene signatures. It can detect tissue heterogeneity in gene expression data. The core algorithm is a Wilcoxon-Mann-Whitney test that is optimised for high performance.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
96 38 exported
Complexity
2.9 avg / 10 max
Call network
96 nodes / 72 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
6,895
Files
111
Compiled share
12.2%
Has compiled src
Yes
Language breakdown
API
Exported functions
39
Internal functions
23
Recent export changes
Testing
Has tests
Yes
Test-to-code ratio
0.37
testthat edition
–
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
3.5.0
System requirements
–
C++ standard
–
License
GPL (>=3) + file LICENSE
License flags
not SPDX, not OSI
History
Versions
21
First release
2016-05-03
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
100%
Dep drift
4
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Help pages
- 54
- Examples that run
- 100%30 run in a plain check
- Exported functions with examples
- 62%
- Documented parameters
- 99%
- Return-value docs
- 62%
- Help pages citing references
- 11%
- BioQC Algorithm: Speeding up the Wilcoxon-Mann-Whitney Test HTML
- BioQC: Detect tissue heterogeneity in gene expression data HTML
- Using BioQC with signed genesets HTML
- BioQC-benchmark: Testing Efficiency, Sensitivity and Specificity of BioQC on simulated and real-world data HTML
- Comparing the Wilcoxon-Mann-Whitney to alternative statistical tests HTML
- BioQC-kidney: The kidney expression example HTML
Repository practices
8 development-tooling and community-health practices detected across 5 families in the upstream repository
Checks run against github.com/accio/bioqc on 2026-10-18.
The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel
GitHub Pages site last deployed 2021-08-24 · The repository has a site deploy workflow
Show all practicesHide 1 practice
Datasets
Topics
People
- Jitao David Zhang maintainer author
- Roland Ambs author
- Laura Badi author
- Iakov Davydov author
- Gregor Sturm author
Cite
Cite this package
Run in R for the authors' entry:
citation("BioQC")The package provides a citation file, so citation() returns the authors' own entry.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.