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knitr::opts_chunk$set( collapse = TRUE, comment = “#>”, fig.path = “man/figures/README-”, out.width = “100%” )

Load the LOCAL package during knitting

devtools::load_all()

##OmicNetR

#OmicNetR is an R package for the integrated analysis of multi-omics datasets using Sparse Canonical Correlation Analysis (sCCA).

#Installation

#You can install the development version of OmicNetR from GitHub:

install.packages(“devtools”)

devtools::install_github(“ppchaudhary/OmicNetR”)

#Quick Start Example

#This example demonstrates how to generate integrated networks and importance plots.

library(OmicNetR)

1. Generate synthetic data

set.seed(123) data <- generate_dummy_omics( n_samples = 60, n_genes = 800, n_metabolites = 150 )

2. Run sCCA

scca_model <- omic_scca( data\(X, data\)Y, penalty_X = 0.7, penalty_Y = 0.7 )

3. Plot bipartite network

net_data <- scca_to_network( scca_model, weight_threshold = 0.05 ) plot_bipartite_network(net_data)

4. Plot circular importance

plot_pathway_circle( scca_model, top_features = 30 )

Biological Interpretation

Nodes

Blue circles represent genes

Orange circles represent metabolites

Edges

Green lines indicate positive correlations

Red lines indicate negative correlations

Contact

Developed by Prem Prashant Chaudhary GitHub ID: ppchaudhary

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.