MEB
Bioc currentA normalization-invariant minimum enclosing ball method to detect differentially expressed genes for RNA-seq and scRNA-seq data
Release Lineage
Entered 3.10 · Oct 30, 2019
Current · Requires R 4.6
Description
This package provides a method to identify differential expression genes in the same or different species. Given that non-DE genes have some similarities in features, a scaling-free minimum enclosing ball (SFMEB) model is built to cover those non-DE genes in feature space, then those DE genes, which are enormously different from non-DE genes, being regarded as outliers and rejected outside the ball. The method on this package is described in the article 'A minimum enclosing ball method to detect differential expression genes for RNA-seq data'. The SFMEB method is extended to the scMEB method that considering two or more potential types of cells or unknown labels scRNA-seq dataset DEGs identification.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
4 2 exported
Complexity
3.3 avg / 5 max
Call network
4 nodes / 2 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
722
Files
21
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
2
Internal functions
2
Testing
Has tests
No
Test-to-code ratio
0.00
testthat edition
–
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
3.6.0
System requirements
–
C++ standard
–
License
GPL-2
License flags
SPDX valid, OSI approved
History
Versions
14
First release
2019-10-29
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
100%
Dep drift
5
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Help pages
- 8
- 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
- 0%
- MEB Tutorial HTML
Repository practices
Checks read the Bioconductor git repository (git.bioconductor.org), branch RELEASE_3_23.
No development-tooling practices detected in the Bioconductor git repository.
Datasets
| Name | Class | Size | Also in |
|---|---|---|---|
| real_data_dsp | – | – | – |
| real_data_sp | – | – | – |
| sim_data_dsp | – | – | – |
| sim_data_sp | – | – | – |
| sim_scRNA_data | – | – | – |
| stable_gene | vector | 1,000 elements | No other package |
Topics
People (from the free-text Author field)
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("MEB")Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
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