WGCNA (Weighted Gene Co-expression Network Analysis) is a classic toolkit in R language used for constructing and analyzing weighted gene co-expression networks. Its core idea is to calculate the expression correlation between genes, build a weighted network, identify highly interconnected gene modules (modules), and correlate these modules with sample traits. WGCNA can reveal the collaborative patterns of gene expression regulation from a global perspective, and identify core genes (hub genes) related to specific biological processes or disease states. This tool is widely applied in transcriptome data mining in complex diseases, developmental biology, plant stress resistance, and other fields.