PyWGCNA is a Python package designed to do Weighted Gene Correlation Network analysis (WGCNA)
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Updated
May 21, 2024 - Jupyter Notebook
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)
An R package for weighted region comethylation network analysis
Code for Walker, Saunders, Rai et al., (2021).
GWAS of Postmortem Brain Samples Sheds Light on the Development of Schizophrenia and Bipolar Disorder
This repository contains a Script for WGCNA based on the Tutorial of WGCNA page
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
Construction of Gene Expression Network across 3 brain regions in the presence of Ethanol using WGCNA in R
Wrapper R scripts for performing a weighted-gene co-expression network analysis (WGCNA)
Code for the (unpublished) paper ( Regulation of autophagy in response to oxidative stress)
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.
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