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

Parkinson's and drug repurposing analysis using WGCNA and Cytoscape. Data at: https://www.ncbi.nlm.nih.gov/sites/GDSbrowser?acc=GDS2821

Weighted Gene Co-expression Network Analysis;

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

Multivariate Analysis Using Co-Expression Network Modeling Identifies Specific Inflammation and Diffusion MRI Features in Major Depressive Disorder

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

Hierarchical, iterative clustering for analysis of transcriptomics data in R

Online app for WGCNA Analysis

My final project of the Master's in Bioinformatics and Computational Biology.

An R package for weighted region comethylation network analysis

Investigate the role of mtDNA in the sex determination/development of Potamilus streckersoni, a freshwater mussel with doubly uniparental mitochondrial inheritance. Scripts for DESeq2, WGCNA, GSEA, AlphaFold/AlphaPulldown, and mt-sncRNA validation.

shiny app for WGCNA...

Experimental code for analysis of miRNA expression in C2C12 vs. in vivo mice cells

Personalized, annotated code for anyone working with RNA-seq data.

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.

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

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

Analysis of PDX BC Dataset for WGCNA module preservation

WGCNA meta-analysis of two breast cancer datasets