Code (pipeline and statistical analysis) used to run Weighted Gene Coexpression Network Analysis on 3500< proteins measured in mice. This project was part of a collaborative effort from the NIH funded Longevity Consortium to identify mechanisms extending lifespan.
WGCNA - R code run in Jupyter Notebooks to analyze MS proteomics data (3969 proteins, 48 samples) - performs soft threshold analysis to optimize parameters for approximating a scale free topology - performs clustering (identification of modules of tightly interconnected proteins in the larger measured network) - calculates module eigenvectors for further statistical analysis