Age-Driven Proteomic Networks in Ningxiang Pig Backfat Identify Candidate Regulators of Carcass Traits

This repository contains the complete R workflow for weighted co-abundance network analysis of the proteomic data from Ningxiang pigs. The analysis identifies key protein modules associated with carcass trait regulation<br>**Analysis Pipeline**:1. Data preprocessing: Normalization and outlier handling2. Soft-threshold selection (power=6, signed hybrid network)3. Module detection (minModuleSize=20, deepSplit=2)4. Module-trait association analysis5. Hub protein identification (top 10 per module)<br>**Key Features**:- Robust correlation: bicor with maxPOutliers=0.1- Visualization: Module dendrograms, trait heatmaps- Output: Adjacency matrices, edge lists for Cytoscape/VisANT<br>**Dependencies**:R packages: WGCNA (v1.72), ggplot2, pheatmap, dplyr<br>For detailed execution, see the README file.