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CoNI

Correlation Guided Network Integration

Short package description:

CoNI is a practical R package for the unsupervised integration of numerical omics datasets. Our tool is based on partial correlations to identify putative confounding variables for a set of paired dependent variables. CoNI combines two omics datasets in an integrated, complex hypergraph-like network, represented as a weighted undirected graph, a bipartite graph, or a hypergraph structure.

Installation

Before installing CoNI a few dependencies are necessary:

dependencies<-c("igraph", "doParallel", "cocor", "tidyverse", "foreach","ggrepel", "gplots", "gridExtra", "plyr", "ppcor", "tidyr", "Hmisc")

`%notin%`<-Negate(`%in%`)
for(package in dependencies){
  if(package %notin% rownames(installed.packages())){
    install.packages(package,dependencies = TRUE)
  }
}

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("genefilter")

Python3 is also required to run CoNI. Make sure it is installed and it is in your path.