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ASURAT

Bioc current

Functional annotation-driven unsupervised clustering for single-cell data

v1.16.0 · Package record · software · GPL-3 + file LICENSE

Release Lineage

Entered 3.15 · Apr 27, 2022

Current · Requires R 4.6

1.0 In 9 of 49 releases 3.23

Description

ASURAT is a software for single-cell data analysis. Using ASURAT, one can simultaneously perform unsupervised clustering and biological interpretation in terms of cell type, disease, biological process, and signaling pathway activity. Inputting a single-cell RNA-seq data and knowledge-based databases, such as Cell Ontology, Gene Ontology, KEGG, etc., ASURAT transforms gene expression tables into original multivariate tables, termed sign-by-sample matrices (SSMs).

Advisories

None published for Bioconductor

Test coverage

Line coverage

–

Expression

–

Tests / Examples

–

Functions

23 17 exported

Complexity

8.2 avg / 27 max

Call network

23 nodes / 5 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

3,437

Files

48

Compiled share

3.5%

Has compiled src

Yes

Language breakdown

R 1,755 (51.1%)C/C++/src 121 (3.5%)Tests 40 (1.2%)Docs 741 (21.6%)Vignettes 780 (22.7%)

API

Exported functions

17

Internal functions

1

Testing

Has tests

Yes

Test-to-code ratio

0.02

testthat edition

3

Docs

Roxygen coverage

100%

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

–

Unsafe pattern score

0

Dep constraint coverage

8.3%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

4.0.0

System requirements

–

C++ standard

–

License

GPL-3 + file LICENSE

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

0

LOC over versions

v3.15: 3,437 LOCv3.16: 3,437 LOCv3.17: 3,437 LOCv3.18: 3,437 LOCv3.19: 3,437 LOCv3.20: 3,437 LOCv3.21: 3,437 LOCv3.22: 3,437 LOCv3.23: 3,437 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 · 86 wordsVignettesYes · 1 · dynamicNEWSYes · 0% structuredCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
23includes a package overview page
Examples that run
100%17 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
0%
Vignettes (1)

Repository practices

Bioconductor git repository

Checks read the Bioconductor git repository (git.bioconductor.org), branch RELEASE_3_23.

No development-tooling practices detected in the Bioconductor git repository.

Datasets

Bundled datasets · 5
NameClassSizeAlso in
human_COMSig_eglist1 elementNo other package
human_GO_eglist4 elementsNo other package
human_KEGG_eglist1 elementNo other package
pbmc_eg–––
pbmcs_eglist3 elements2 packages

All of ASURAT's data objects

Topics

Maintainer
Keita Iida

Available on

CRANr2uBioconductorautoCRANCOPR

People

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("ASURAT")
Iida, K., & Wibisana, J. N. (2026). ASURAT: Functional annotation-driven unsupervised clustering for single-cell data (Version 1.16.0) [Computer software]. https://bioconductor.org/packages/ASURAT

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 ASURAT version 1.16.0 [Data set]. HJJB, LLC. Data release v2026-10-26. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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