POMA
Bioc currentTools for Omics Data Analysis
Release Lineage
Entered 3.12 · Oct 28, 2020
Current · Requires R 4.6
Description
The POMA package offers a comprehensive toolkit designed for omics data analysis, streamlining the process from initial visualization to final statistical analysis. Its primary goal is to simplify and unify the various steps involved in omics data processing, making it more accessible and manageable within a single, intuitive R package. Emphasizing on reproducibility and user-friendliness, POMA leverages the standardized SummarizedExperiment class from Bioconductor, ensuring seamless integration and compatibility with a wide array of Bioconductor tools. This approach guarantees maximum flexibility and replicability, making POMA an essential asset for researchers handling omics datasets. See https://github.com/pcastellanoescuder/POMAShiny. Paper: Castellano-Escuder et al. (2021) <doi:10.1371/journal.pcbi.1009148> for more details.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
44 32 exported
Complexity
7.2 avg / 24 max
Call network
44 nodes / 40 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
7,720
Files
112
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
33
Internal functions
12
Recent export changes
Testing
Has tests
Yes
Test-to-code ratio
0.19
testthat edition
–
Docs
Roxygen coverage
97%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
0
Dep constraint coverage
3%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.0
System requirements
–
C++ standard
–
License
GPL-3
License flags
SPDX valid, OSI approved
History
Versions
12
First release
2020-10-27
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
100%
Dep drift
31
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Help pages
- 41 (1 internal)
- Examples that run
- 92%24 run in a plain check · 1 never run · 1 hold no code
- Exported functions with examples
- 79%
- Documented parameters
- 94%
- Return-value docs
- 78%
- Help pages citing references
- 27%
- Normalization Methods HTML
- Get Started HTML
Repository practices
6 development-tooling and community-health practices detected across 4 families in the upstream repository
Checks run against github.com/pcastellanoescuder/poma on 2026-10-18.
The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel
GitHub Pages site last deployed 2022-07-09
Datasets
Topics
Depended on by (1)
Bioconductor (1)
Suggested by (1)
People
- Pol Castellano-Escuder author maintainer
Cite
Cite this package
Run in R for the authors' entry:
citation("POMA")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1371/journal.pcbi.1009148.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.