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CellTrails

Bioc current

Reconstruction, visualization and analysis of branching trajectories

v1.30.0 · software · Artistic-2.0

Release Lineage

Entered 3.8 · Oct 31, 2018

Current · Requires R 4.6

1.0 In 16 of 49 releases 3.23

Description

CellTrails is an unsupervised algorithm for the de novo chronological ordering, visualization and analysis of single-cell expression data. CellTrails makes use of a geometrically motivated concept of lower-dimensional manifold learning, which exhibits a multitude of virtues that counteract intrinsic noise of single cell data caused by drop-outs, technical variance, and redundancy of predictive variables. CellTrails enables the reconstruction of branching trajectories and provides an intuitive graphical representation of expression patterns along all branches simultaneously. It allows the user to define and infer the expression dynamics of individual and multiple pathways towards distinct phenotypes.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

53 3 exported

Complexity

4 avg / 26 max

Call network

53 nodes / 24 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

10,469

Files

170

Compiled share

0%

Has compiled src

No

Language breakdown

R 6,184 (59.1%)Tests 1 (0%)Docs 4,251 (40.6%)Vignettes 33 (0.3%)

API

Exported functions

48

Internal functions

50

Recent export changes

v3.8+48 latentSpace<-, manifold2D<-, stateTrajLayout<- +45 more

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

0%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

3.5

System requirements

C++ standard

License

Artistic-2.0

License flags

SPDX valid, OSI approved

History

Versions

16

First release

2019-01-04

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

Dep drift

0

LOC over versions

v3.8: 8,700 LOCv3.9: 8,700 LOCv3.10: 8,700 LOCv3.11: 10,469 LOCv3.12: 10,469 LOCv3.13: 10,469 LOCv3.14: 10,469 LOCv3.15: 10,469 LOCv3.16: 10,469 LOCv3.17: 10,469 LOCv3.18: 10,469 LOCv3.19: 10,469 LOCv3.20: 10,469 LOCv3.21: 10,469 LOCv3.22: 10,469 LOCv3.23: 10,469 LOC

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

Documentation

Documentation
READMEYes · 681 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 67% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
5%

Topics

People

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("CellTrails")
Ellwanger, D. (2026). CellTrails: Reconstruction, visualization and analysis of branching trajectories (Version 1.30.0) [Computer software]. https://bioconductor.org/packages/CellTrails

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 CellTrails version 1.30.0 [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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