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proBatch

Bioc current

Tools for Diagnostics and Corrections of Batch Effects in Proteomics

v2.0.0 · software · GPL-3

Release Lineage

Entered 3.9 · May 3, 2019

Current · Requires R 4.6

1.0 In 15 of 49 releases 3.23

Description

These tools facilitate batch effects analysis and correction in high-throughput experiments. It was developed primarily for mass-spectrometry proteomics (DIA/SWATH), but could also be applicable to most omic data with minor adaptations. The package contains functions for diagnostics (proteome/genome-wide and feature-level), correction (normalization and batch effects correction) and quality control. Non-linear fitting based approaches were also included to deal with complex, mass spectrometry-specific signal drifts.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

185 86 exported

Complexity

5.5 avg / 34 max

Call network

185 nodes / 282 edges

Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.

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Lowest coverage

Per-function coverage is not measured for this package yet.

Code

Structure

Lines of code

21,145

Files

133

Compiled share

0%

Has compiled src

No

Language breakdown

R 9,537 (45.1%)Tests 3,275 (15.5%)Docs 6,181 (29.2%)Vignettes 2,152 (10.2%)

API

Exported functions

86

Internal functions

98

Recent export changes

v3.9+30 adjust_batch_trend, center_peptide_batch_medians, correct_batch_effects +27 more
v3.23+28 ProBatchFeatures, ProBatchFeatures_from_long, convert_annotation_classes +25 more

Testing & CI

Has tests

Yes

Test-to-code ratio

0.34

testthat edition

3

CI present

No

CI type

[]

PR gated

No

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-3

License flags

SPDX valid, OSI approved

History

Versions

10

First release

2019-05-02

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

100%

Dep drift

9

LOC over versions

v3.9: 6,634 LOCv3.10: 9,954 LOCv3.11: 10,381 LOCv3.12: 10,381 LOCv3.13: 10,381 LOCv3.14: 10,381 LOCv3.15: 10,381 LOCv3.16: 10,381 LOCv3.17: 10,387 LOCv3.23: 21,145 LOC

Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.

Documentation

Documentation
READMEYes · 234 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 33% structuredCode of conductNoContributing guideNo
Examples that run
98%
Documented parameters
95%
Return-value docs
100%
References docs
0%

Topics

People

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("proBatch")
Burankova, Y., Cuklina, J., Lee, C. H., Pedrioli, P., & Zolotareva, O. (2026). proBatch: Tools for Diagnostics and Corrections of Batch Effects in Proteomics (Version 2.0.0) [Computer software]. https://bioconductor.org/packages/proBatch

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.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for proBatch version 2.0.0 [Data set]. HJJB, LLC. Data release v2026-08-23. https://doi.org/10.5281/zenodo.21843040

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.

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