proDA
Bioc currentDifferential Abundance Analysis of Label-Free Mass Spectrometry Data
Release Lineage
Entered 3.10 · Oct 30, 2019
Current · Requires R 4.6
Description
Account for missing values in label-free mass spectrometry data without imputation. The package implements a probabilistic dropout model that ensures that the information from observed and missing values are properly combined. It adds empirical Bayesian priors to increase power to detect differentially abundant proteins.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
39 8 exported
Complexity
7.1 avg / 35 max
Call network
39 nodes / 48 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
6,148
Files
123
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
17
Internal functions
30
Testing & CI
Has tests
Yes
Test-to-code ratio
0.31
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
3
Dep constraint coverage
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
–
System requirements
–
C++ standard
–
License
GPL-3
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
–
Dep drift
0
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
- 94%
- Return-value docs
- 100%
- References docs
- 0%
Topics
Depended on by (3)
Bioconductor (2)
CRAN (1)
People
- Constantin Ahlmann-Eltze author maintainer
- Simon Anders ths
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("proDA")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.