msqrob2
Bioc currentRobust statistical inference for quantitative LC-MS proteomics
Release Lineage
Entered 3.13 · May 20, 2021
Current · Requires R 4.6
Description
msqrob2 provides a robust linear mixed model framework for assessing differential abundance in MS-based Quantitative proteomics experiments. Our workflows can start from raw peptide intensities or summarised protein expression values. The model parameter estimates can be stabilized by ridge regression, empirical Bayes variance estimation and robust M-estimation. msqrob2's hurde workflow can handle missing data without having to rely on hard-to-verify imputation assumptions, and, outcompetes state-of-the-art methods with and without imputation for both high and low missingness. It builds on QFeature infrastructure for quantitative mass spectrometry data to store the model results together with the raw data and preprocessed data.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
31 10 exported
Complexity
6.2 avg / 73 max
Call network
31 nodes / 25 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
8,585
Files
58
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
31
Internal functions
21
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.01
testthat edition
–
CI present
Yes
CI type
["github-actions"]
PR gated
Yes
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
0
Dep constraint coverage
5.3%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.1
System requirements
–
C++ standard
–
License
Artistic-2.0
License flags
SPDX valid, OSI approved
History
Versions
11
First release
2021-05-19
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
–
Dep drift
8
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
- 76%
- Return-value docs
- 100%
- References docs
- 5%
Topics
People
- Lieven Clement author maintainer
- Oliver M. Crook author
- Laurent Gatto author
- Ludger Goeminne contributor
- Milan Malfait contributor
- Adriaan Sticker contributor
- Stijn Vandenbulcke author
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("msqrob2")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.