CRAN/E | modACDC

modACDC

Association of Covariance for Detecting Differential Co-Expression

Installation

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.

github.com/USCbiostats/ACDC

Key Metrics

Version 2.0.1
R ≥ 4.1.0
Published 2024-01-30 90 days ago
Needs compilation? no
License MIT
License File
CRAN checks modACDC results

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Maintainer

Maintainer

Katelyn Queen

kjqueen@usc.edu

Authors

Katelyn Queen

aut / cre / cph

Joshua Millstein

aut / cph

Material

README
NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

modACDC archive

Depends

R ≥ 4.1.0

Imports

CCP
data.table
doParallel
foreach
genieclust
genio
ggplot2
partition
parallel
tibble
tidyr
tools
utils

Suggests

CCA