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qmtools

Bioc current

Quantitative Metabolomics Data Processing Tools

v1.16.0 · Package record · software · GPL-3

Release Lineage

Entered 3.15 · Apr 27, 2022

Current · Requires R 4.6

1.0 In 9 of 49 releases 3.23

Description

The qmtools (quantitative metabolomics tools) package provides basic tools for processing quantitative metabolomics data with the standard SummarizedExperiment class. This includes functions for imputation, normalization, feature filtering, feature clustering, dimension-reduction, and visualization to help users prepare data for statistical analysis. This package also offers a convenient way to compute empirical Bayes statistics for which metabolic features are different between two sets of study samples. Several functions in this package could also be used in other types of omics data.

Advisories

None published for Bioconductor

Test coverage

Line coverage

–

Expression

–

Tests / Examples

–

Functions

63 18 exported

Complexity

4.2 avg / 70 max

Call network

63 nodes / 54 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

5,609

Files

59

Compiled share

0%

Has compiled src

No

Language breakdown

R 3,006 (53.6%)Tests 370 (6.6%)Docs 1,877 (33.5%)Vignettes 356 (6.3%)

API

Exported functions

22

Internal functions

44

Testing

Has tests

Yes

Test-to-code ratio

0.12

testthat edition

3

Docs

Roxygen coverage

100%

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

50%

Unsafe pattern score

0

Dep constraint coverage

0%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

4.2.0

System requirements

–

C++ standard

–

License

GPL-3

License flags

SPDX valid, OSI approved

History

Versions

9

First release

2022-04-26

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

–

Dep drift

1

LOC over versions

v3.15: 5,225 LOCv3.16: 5,225 LOCv3.17: 5,561 LOCv3.18: 5,561 LOCv3.19: 5,609 LOCv3.20: 5,609 LOCv3.21: 5,609 LOCv3.22: 5,609 LOCv3.23: 5,609 LOC

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

Documentation

In the Bioconductor 3.23 release
READMEYes · 53 wordsVignettesYes · 1 · dynamicNEWSYes · 100% structuredCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
24 (1 internal)includes a package overview page
Examples that run
100%23 run in a plain check
Exported functions with examples
100%
Documented parameters
96%
Return-value docs
100%
Help pages citing references
67%

Repository practices

Upstream repositoryBeta

Checks run against github.com/himesgroup/qmtools on 2026-10-18.

No development-tooling practices detected in the upstream repository.

How this is detected·Detection ruleset v3 (2026-09-26)

Datasets

Bundled datasets · 1
NameClassSizeAlso in
faahko_se–––

All of qmtools's data objects

Topics

Maintainer
Jaehyun Joo

Available on

CRANr2uBioconductorautoCRANCOPR

People

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("qmtools")
Joo, J., & Himes, B. (2026). qmtools: Quantitative Metabolomics Data Processing Tools (Version 1.16.0) [Computer software]. https://bioconductor.org/packages/qmtools

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

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 qmtools version 1.16.0 [Data set]. HJJB, LLC. Data release v2026-10-21. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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