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immApex

Bioc current

Tools for Adaptive Immune Receptor Sequence-Based Machine and Deep Learning

v1.6.0 · software · MIT + file LICENSE

Release Lineage

Entered 3.20 · Oct 30, 2024

Current · Requires R 4.6

1.0 In 4 of 49 releases 3.23

Description

A set of tools to for machine and deep learning in R from amino acid and nucleotide sequences focusing on adaptive immune receptors. The package includes pre-processing of sequences, unifying gene nomenclature usage, encoding sequences, and combining models. This package will serve as the basis of future immune receptor sequence functions/packages/models compatible with the scRepertoire ecosystem.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

86 35 exported

Complexity

5.4 avg / 37 max

Call network

86 nodes / 52 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

8,928

Files

125

Compiled share

8.2%

Has compiled src

Yes

Language breakdown

R 3,324 (37.2%)C/C++/src 735 (8.2%)Tests 2,347 (26.3%)Docs 1,752 (19.6%)Vignettes 770 (8.6%)

API

Exported functions

36

Internal functions

33

Recent export changes

v3.22+21 ace_richness, amino.acids, buildNetwork +18 more
v3.20+15 adjacencyMatrix, formatGenes, generateSequences +12 more

Testing & CI

Has tests

Yes

Test-to-code ratio

0.71

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

0%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

4.3.0

System requirements

C++ standard

C++17

License

MIT + file LICENSE

License flags

SPDX valid, OSI approved

History

Versions

4

First release

2025-02-25

Latest release

2026-04-28

Avg cadence

144 days

Cold removal rate

Dep drift

13

LOC over versions

v3.20: 4,029 LOCv3.21: 4,051 LOCv3.22: 8,983 LOCv3.23: 8,928 LOC

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

Documentation

Documentation
READMEYes · 386 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
93%
Documented parameters
98%
Return-value docs
97%
References docs
5%

Topics

Depended on by (4)

Bioconductor (4)

People

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("immApex")
Borcherding, N., & Yang, Q. (2026). immApex: Tools for Adaptive Immune Receptor Sequence-Based Machine and Deep Learning (Version 1.6.0) [Computer software]. https://bioconductor.org/packages/immApex

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 immApex version 1.6.0 [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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