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MSstatsPTM

Bioc current

Statistical Characterization of Post-translational Modifications

v2.14.0 · software · Artistic-2.0

Release Lineage

Entered 3.12 · Oct 28, 2020

Current · Requires R 4.6

1.0 In 12 of 49 releases 3.23

Description

MSstatsPTM provides general statistical methods for quantitative characterization of post-translational modifications (PTMs). Supports DDA, DIA, SRM, and tandem mass tag (TMT) labeling. Typically, the analysis involves the quantification of PTM sites (i.e., modified residues) and their corresponding proteins, as well as the integration of the quantification results. MSstatsPTM provides functions for summarization, estimation of PTM site abundance, and detection of changes in PTMs across experimental conditions.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

95 22 exported

Complexity

6 avg / 32 max

Call network

95 nodes / 89 edges

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

Loading call graph…

Lowest coverage

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

Code

Structure

Lines of code

11,738

Files

234

Compiled share

0.6%

Has compiled src

Yes

Language breakdown

R 8,014 (68.3%)C/C++/src 70 (0.6%)Tests 4 (0%)Docs 3,068 (26.1%)Vignettes 582 (5%)

API

Exported functions

22

Internal functions

70

Recent export changes

v3.22+2 ProteinProspectortoMSstatsPTMFormat, dataProcessPTM
v3.19+1 MetamorpheusToMSstatsPTMFormat

Testing & CI

Has tests

Yes

Test-to-code ratio

0.00

testthat edition

3

CI present

Yes

CI type

["github-actions","travis"]

PR gated

Yes

Docs

Roxygen coverage

100%

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

Unsafe pattern score

0

Dep constraint coverage

5.6%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

4.3

System requirements

C++ standard

License

Artistic-2.0

License flags

SPDX valid, OSI approved

History

Versions

12

First release

2020-10-27

Latest release

2026-04-28

Avg cadence

181 days

Cold removal rate

100%

Dep drift

20

LOC over versions

v3.12: 2,638 LOCv3.13: 6,594 LOCv3.14: 6,665 LOCv3.15: 6,665 LOCv3.16: 8,924 LOCv3.17: 9,945 LOCv3.18: 10,287 LOCv3.19: 10,666 LOCv3.20: 10,718 LOCv3.21: 10,734 LOCv3.22: 11,690 LOCv3.23: 11,738 LOC

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

Documentation

Documentation
READMEYes · 125 wordsVignettesYes · dynamicpkgdown siteYesNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
80%
Return-value docs
95%
References docs
0%

Topics

Depended on by (2)

Bioconductor (2)

People

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("MSstatsPTM")
Wu, A., Choi, M., Huang, T., Kohler, D., Raju, D., Staniak, M., Tsai, T., & Vitek, O. (2026). MSstatsPTM: Statistical Characterization of Post-translational Modifications (Version 2.14.0) [Computer software]. https://bioconductor.org/packages/MSstatsPTM

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 MSstatsPTM version 2.14.0 [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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