PyWGCNA is a Python package designed to do Weighted Gene Correlation Network analysis (WGCNA)

Hierarchical, iterative clustering for analysis of transcriptomics data in R

A step-by-step tutorial for Weighted correlation network analysis (WGCNA)

shiny app for WGCNA...

An R package for weighted region comethylation network analysis

This repository contains a Script for WGCNA based on the Tutorial of WGCNA page

GWAS of Postmortem Brain Samples Sheds Light on the Development of Schizophrenia and Bipolar Disorder

Code for Walker, Saunders, Rai et al., (2021).

Online app for WGCNA Analysis

Algorithms for NCBI, SRA, EBI datasets recommendation and how to get around with comparing your own Datasets. Recommender systems | Bio-NLP

Differential Expression Analysis of protein, Gene set enrichment analysis, Multi-omic factor analysis, Pathway analysis, WGCNA

Construction of Gene Expression Network across 3 brain regions in the presence of Ethanol using WGCNA in R

Weighted Gene Co-expression Network Analysis;

attempt a non-bash pipeline in nextflow

Wrapper R scripts for performing a weighted-gene co-expression network analysis (WGCNA)

Gene expression and network analysis for multiple RNA-seq datasets associated with heat-stress in abalone

Repository for all R scripts and results associated with my research dissertation for the MSc Bioinformatics and Computational Biology degree in University College Cork, 2022.