Embark on a comprehensive step-by-step tutorial exploring Weighted Gene Co-expression Network Analysis (WGCNA) using RNA-Seq data. Learn data manipulation techniques, outlier detection methods for genes and samples, normalization procedures, soft threshold selection, module identification, and dendrogram visualization. Follow along as the instructor demonstrates each step using R, covering topics such as data retrieval, metadata extraction with GEOquery, quality control measures, hierarchical clustering, Principal Component Analysis (PCA), data normalization with DESeq2, gene filtering, and module eigengene calculation. Gain practical insights into WGCNA workflow and its application in analyzing gene co-expression networks.