IPO
Bioc currentAutomated Optimization of XCMS Data Processing parameters
Release Lineage
Entered 3.4 · Oct 18, 2016
Current · Requires R 4.6
Description
The outcome of XCMS data processing strongly depends on the parameter settings. IPO (`Isotopologue Parameter Optimization`) is a parameter optimization tool that is applicable for different kinds of samples and liquid chromatography coupled to high resolution mass spectrometry devices, fast and free of labeling steps. IPO uses natural, stable 13C isotopes to calculate a peak picking score. Retention time correction is optimized by minimizing the relative retention time differences within features and grouping parameters are optimized by maximizing the number of features showing exactly one peak from each injection of a pooled sample. The different parameter settings are achieved by design of experiment. The resulting scores are evaluated using response surface models.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
48 21 exported
Complexity
4.5 avg / 21 max
Call network
48 nodes / 67 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
3,640
Files
41
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
21
Internal functions
20
Testing & CI
Has tests
Yes
Test-to-code ratio
0.00
testthat edition
–
CI present
Yes
CI type
["travis"]
PR gated
No
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
0%
Unsafe pattern score
0
Dep constraint coverage
12.5%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
–
System requirements
–
C++ standard
–
License
GPL (>= 2) + file LICENSE
License flags
SPDX valid, OSI approved
History
Versions
20
First release
2016-10-17
Latest release
2026-04-28
Avg cadence
181 days
Cold removal rate
–
Dep drift
1
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Examples that run
- 77%
- Documented parameters
- 97%
- Return-value docs
- 100%
- References docs
- 36%
Topics
People
Thomas Lieb
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("IPO")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.