WGCNA Explained: A Guide for Clinicians by a Bioinformatician

WGCNA (Weighted Gene Co-expression Network Analysis) is a bioinformatics method used to identify co-expressed gene modules within gene expression data and connect these modules to biological processes and diseases. This method can analyze large-scale gene expression datasets, including microarray and RNA sequencing data, and generate a series of co-expressed gene modules, each containing highly correlated genes. WGCNA utilizes weighted correlation coefficients to calculate the similarity between genes and clusters similar genes into modules. These modules can be used to identify key genes involved in biological processes and diseases, providing new biological insights and therapeutic targets for research. WGCNA has been widely applied in biomedical research, such as discovering cancer biomarkers, predicting drug response, and investigating neurological diseases.