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modACDC

Association of covariance to detect differential co-expression

https://github.com/uscbiostats/acdc

Science Score: 54.0%

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    Found 1 DOI reference(s) in README
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    Links to: frontiersin.org
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    Committers with academic emails
    1 of 2 committers (50.0%) from academic institutions
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    Institutional organization owner
    Organization uscbiostats has institutional domain (biostatsepi.usc.edu)
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    Low similarity (11.0%) to scientific vocabulary
Last synced: 7 months ago · JSON representation

Repository

Association of covariance to detect differential co-expression

Basic Info
  • Host: GitHub
  • Owner: USCbiostats
  • License: other
  • Language: R
  • Default Branch: main
  • Homepage:
  • Size: 264 KB
Statistics
  • Stars: 1
  • Watchers: 5
  • Forks: 0
  • Open Issues: 0
  • Releases: 2
Created about 3 years ago · Last pushed almost 2 years ago
Metadata Files
Readme Changelog License

README.md

CRAN status CRAN downloads status

modACDC

Association of covariance to detect differential co-expression (ACDC) is a novel approach for detection of differential co-expression that simultaneously accommodates multiple phenotypes or exposures with binary, ordinal, or continuous data types. The default method (ACDC) identifies modules using Partition and the modACDC method allows users to 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) or Genome-wide Complex Trait Analysis (GCTA).

The manuscript for ACDC can be found here.

Installation

You can install modACDC directly from CRAN with:

r install.packages("modACDC")

Or you can install the development, GitHub version with:

```{r}

install.packages("remotes")

remotes::install_github("USCbiostats/ACDC") ```

OSCA

OSCA is a suite of C++ functions that provides an estimate of the percent of variance in an external phenotype that can be explained by an omics profile, akin to heritability estimates in GWAS. Here, we make calls to OSCA's Omics Restricted Maximum Likelihood (OREML) method.

In order to use the OSCA functions, the user must specify the absolute path to the OSCA software, which can be downloaded from the Yang Lab website here.

GCTA

GCTA is a suite of C++ functions that provides an estimate of the heritability of a trait. Here, we make calls to GCTA's Genomics REstricted Maximum Likelihood (GREML) method.

In order to use the GCTA functions, the user must specify the absolute path to the GCTA software, which can be downloaded from the Yang Lab website here.

Owner

  • Name: USC Division of Biostatistics
  • Login: USCbiostats
  • Kind: organization
  • Location: Los Angeles, CA

GitHub Events

Total
Last Year

Committers

Last synced: 10 months ago

All Time
  • Total Commits: 95
  • Total Committers: 2
  • Avg Commits per committer: 47.5
  • Development Distribution Score (DDS): 0.011
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
katelynqueen98 k****n@u****u 94
Paul Marjoram p****a@g****m 1
Committer Domains (Top 20 + Academic)
usc.edu: 1

Issues and Pull Requests

Last synced: 8 months ago

All Time
  • Total issues: 1
  • Total pull requests: 0
  • Average time to close issues: about 6 hours
  • Average time to close pull requests: N/A
  • Total issue authors: 1
  • Total pull request authors: 0
  • Average comments per issue: 0.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • katelynqueen98 (1)
Pull Request Authors
Top Labels
Issue Labels
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Packages

  • Total packages: 1
  • Total downloads:
    • cran 260 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 3
  • Total maintainers: 1
cran.r-project.org: modACDC

Association of Covariance for Detecting Differential Co-Expression

  • Versions: 3
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 260 Last month
Rankings
Forks count: 28.3%
Dependent packages count: 28.3%
Stargazers count: 34.9%
Dependent repos count: 36.9%
Average: 37.5%
Downloads: 59.0%
Maintainers (1)
kjqueen@usc.edu
Last synced: 8 months ago

Dependencies

DESCRIPTION cran
  • R >= 4.1.0 depends
  • CCA * imports
  • CCP * imports
  • data.table * imports
  • doParallel * imports
  • foreach * imports
  • ggplot2 * imports
  • parallel * imports
  • partition * imports
  • stats * imports
  • tidyr * imports
  • utils * imports