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CTSV

Bioc current

Identification of cell-type-specific spatially variable genes accounting for excess zeros

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

The R package CTSV implements the CTSV approach developed by Jinge Yu and Xiangyu Luo that detects cell-type-specific spatially variable genes accounting for excess zeros. CTSV directly models sparse raw count data through a zero-inflated negative binomial regression model, incorporates cell-type proportions, and performs hypothesis testing based on R package pscl. The package outputs p-values and q-values for genes in each cell type, and CTSV is scalable to datasets with tens of thousands of genes measured on hundreds of spots. CTSV can be installed in Windows, Linux, and Mac OS.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

3 2 exported

Complexity

9.7 avg / 22 max

Call network

3 nodes / 0 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

558

Files

14

Compiled share

0%

Has compiled src

No

Language breakdown

R 183 (32.8%)Tests 70 (12.5%)Docs 181 (32.4%)Vignettes 124 (22.2%)

API

Exported functions

2

Internal functions

1

Testing & CI

Has tests

Yes

Test-to-code ratio

0.38

testthat edition

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

4.2

System requirements

C++ standard

License

GPL-3

License flags

SPDX valid, OSI approved

History

Versions

8

First release

2022-11-01

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

Dep drift

0

LOC over versions

v3.16: 558 LOCv3.17: 558 LOCv3.18: 558 LOCv3.19: 558 LOCv3.20: 558 LOCv3.21: 558 LOCv3.22: 558 LOCv3.23: 558 LOC

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

Documentation

Documentation
READMEYes · 180 wordsVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
67%
Documented parameters
100%
Return-value docs
100%
References docs
0%

Topics

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