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modACDC

2.0.1Package record

Association of Covariance for Detecting Differential Co-Expression

0packages depend
2.8Kdownloads / year
–test coverage
11/13flavors OK

Overview

About

A series of functions to implement association of covariance for detecting differential co-expression (ACDC), a novel approach for detection of differential co-expression that simultaneously accommodates multiple phenotypes or exposures with binary, ordinal, or continuous data types. Users can use the default method which identifies modules by Partition or may supply their own modules. Also included are functions to choose an information loss criterion (ILC) for Partition using OmicS-data-based Complex trait Analysis (OSCA) and Genome-wide Complex trait Analysis (GCTA). The manuscript describing these methods is as follows: Queen K, Nguyen MN, Gilliland F, Chun S, Raby BA, Millstein J. "ACDC: a general approach for detecting phenotype or exposure associated co-expression" (2023) doi:10.3389/fmed.2023.1118824.

Install

Health

CRAN checks
2NOTE11OK
Check messages
NOTEdependencies in R coder-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Namespace in Imports field not imported from:
  ‘tibble’
All declared Imports should be used.

CRAN check page ↗

Slowest check: 2.0 min · r-oldrel-windows-x86_64
Status changes
  • NOTE11 OK, 2 NOTE2026-06-09
  • ERROR10 OK, 2 NOTE, 1 ERROR2026-06-08
  • NOTE12 OK, 2 NOTE2026-03-10
Advisories

none known

Documentation

In release 2.0.1
READMEYes · 239 wordsVignettesNoNEWSYes · 100% structured · does not mention 2.0.1Citation fileNoWebsitenot declared in DESCRIPTION
Help pages
10
Examples that run
80%8 run in a plain check · 2 never run
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
100%

Downloads

2.8K
CRAN downloads in the past year
Rank #20,625 · ~8/day · ~233/mo
Daily download trend is not available in this view yet.
26630 days
64790 days
2.8K1 year
Compare downloads with other packages →
Also on67 r2u4 autocran

Repository

1Stars
0Forks
0Open issues
0Open PRs
2Releases
98Commits
2Commit identities
98 commits · Last activity 2024-04-09
Responsiveness
How these are sampled
PRs merged (all time)
not measured
Median days to close, 50 most recently updated closed issues
1
Median days to close, 50 most recently updated closed PRs
not measured

Stars over time

2024-03-26 · 12026-07-07 · 1
PracticesBeta

3 development-tooling and community-health practices detected across 2 families in the upstream repository

Checks run against github.com/uscbiostats/acdc on 2026-10-21.

CRAN release process (2)
cran-comments.mdCRAN-SUBMISSION
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
11 external dependencies (excludes base and recommended)

Installing modACDC adds 53 packages (29 with compiled code, 42 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.

Depends (1)
R >= 4.1.0
LinkingTo (0)
none
Suggests (1)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (2)
Author, Maintainer since 1.0.0 (2023), Copyright holder
Author, Copyright holder
Releases (3)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • 2.0.1Latest
    record
    2024-01-30 · current release · diff ↗
  • 2.0.0
    record
    2024-01-25 · diff ↗ ·
    added 3 exports
    GCTA_par, GCTA_parPlot, GCTA_singleValue
  • 1.0.0
    record
    2023-05-10
  • R
    R 4.3.0 released · 2023-04-21

Package metadata

First published
2023-05-10
Total releases
3 / 3 yrs
License
MIT + file LICENSE OSI
Minimum R
≥ 4.1.0
Download size
20 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("modACDC")
Queen, K., & Millstein, J. (2024). modACDC: Association of Covariance for Detecting Differential Co-Expression (Version 2.0.1) [Computer software]. https://doi.org/10.32614/CRAN.package.modACDC

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 modACDC version 2.0.1 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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