LimROTS
Bioc currentLimROTS: A Hybrid Method Integrating Empirical Bayes and Reproducibility-Optimized Statistics for Robust Differential Expression Analysis
Release Lineage
Entered 3.21 · Apr 16, 2025
Current · Requires R 4.6
Description
Differential expression analysis is commonly used to study diverse biological datasets. The reproducibility-optimized test statistic (ROTS) (Elo et al., 2008, <doi:10.1109/tcbb.2007.1078>) uses a modified t-statistic to prioritise features that differ between two or more groups. However, the ROTS Bioconductor implementation (Suomi et al., 2017, <doi:10.1371/journal.pcbi.1005562>) did not accommodate technical or biological covariates. LimROTS (Anwar et al., 2025, <doi:10.1093/bioinformatics/btaf570>) addressed this limitation by combining a reproducibility-optimized test statistic with the limma empirical Bayes approach (Ritchie et al., 2015, <doi:10.1093/nar/gkv007>). This enables the analysis of more complex experimental designs and the incorporation of covariates.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
22 2 exported
Complexity
6.9 avg / 19 max
Call network
22 nodes / 24 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
5,767
Files
60
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
2
Internal functions
17
Recent export changes
Testing
Has tests
Yes
Test-to-code ratio
0.17
testthat edition
3
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
0
Dep constraint coverage
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.5.0
System requirements
–
C++ standard
–
License
GPL (>= 2)
License flags
SPDX valid, OSI approved
History
Versions
3
First release
2025-06-16
Latest release
2026-04-28
Avg cadence
158 days
Cold removal rate
–
Dep drift
3
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Help pages
- 23
- Examples that run
- 100%2 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 13%
Repository practices
2 development-tooling and community-health practices detected across 2 families in the upstream repository
Checks run against github.com/aliyoussef96/limrots on 2026-10-21.
GitHub Pages site last deployed 2026-04-30
Datasets
Topics
People
- Ali Mostafa Anwar author maintainer
- Eleanor Coffey author thesis advisor
- Rasmus Hindström contributor
- Akewak Jeba author contributor
- Leo Lahti author thesis advisor
Cite
Cite this package
Run in R for the authors' entry:
citation("LimROTS")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1093/bioinformatics/btaf570.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.