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ccImpute

Bioc current

ccImpute: an accurate and scalable consensus clustering based approach to impute dropout events in the single-cell RNA-seq data (https://doi.org/10.1186/s12859-022-04814-8)

v1.14.0 · software · GPL-3

Release Lineage

Entered 3.16 · Nov 2, 2022

Current · Requires R 4.6

1.0 In 8 of 49 releases 3.23

Description

Dropout events make the lowly expressed genes indistinguishable from true zero expression and different than the low expression present in cells of the same type. This issue makes any subsequent downstream analysis difficult. ccImpute is an imputation algorithm that uses cell similarity established by consensus clustering to impute the most probable dropout events in the scRNA-seq datasets. ccImpute demonstrated performance which exceeds the performance of existing imputation approaches while introducing the least amount of new noise as measured by clustering performance characteristics on datasets with known cell identities.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

41 8 exported

Complexity

2.1 avg / 9 max

Call network

41 nodes / 35 edges

Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.

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Lowest coverage

Per-function coverage is not measured for this package yet.

Code

Structure

Lines of code

2,196

Files

41

Compiled share

24.2%

Has compiled src

Yes

Language breakdown

R 624 (28.4%)C/C++/src 531 (24.2%)Tests 30 (1.4%)Docs 688 (31.3%)Vignettes 323 (14.7%)

API

Exported functions

9

Internal functions

10

Recent export changes

v3.19+8 ccImpute.SingleCellExperiment, computeDropouts, doSVD +5 more

Testing & CI

Has tests

Yes

Test-to-code ratio

0.05

testthat edition

3

CI present

No

CI type

[]

PR gated

No

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

System requirements

C++ standard

C++11

License

GPL-3

License flags

SPDX valid, OSI approved

History

Versions

8

First release

2023-01-19

Latest release

2026-04-28

Avg cadence

176 days

Cold removal rate

Dep drift

7

LOC over versions

v3.16: 994 LOCv3.17: 994 LOCv3.18: 994 LOCv3.19: 2,196 LOCv3.20: 2,196 LOCv3.21: 2,196 LOCv3.22: 2,196 LOCv3.23: 2,196 LOC

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

Documentation

Documentation
READMEYes · 426 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 33% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
0%

Topics

People

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("ccImpute")
Malec, M., Dalkilic, M., Kurban, H., & Sharma, P. (2026). ccImpute: ccImpute: an accurate and scalable consensus clustering based approach to impute dropout events in the single-cell RNA-seq data (https://doi.org/10.1186/s12859-022-04814-8) (Version 1.14.0) [Computer software]. https://bioconductor.org/packages/ccImpute

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 ccImpute version 1.14.0 [Data set]. HJJB, LLC. Data release v2026-08-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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