Source Code and Processed Data for Clustering Analysis of Giant Cell Arteritis Using Varicella-Zoster Virus-Human Interacting Proteins

Monte Carlo simulation with 10,000 repeated random samplings was used to evaluate the statistical significance of the observed clustering effect, with all analytical parameters kept consistent between the target protein set and random gene/protein sets.Contents of the zipped packageThe single compressed archive includes:Full R scripts covering the entire workflow: data preprocessing, spectral clustering implementation, silhouette coefficient calculation, and Monte Carlo permutation testPreprocessed expression matrices of all four included datasetsOutput result files of clustering analysis and statistical significance testsA README file illustrating the directory structure, required runtime environment, dependent packages, and step-by-step reproduction instructionsSoftware environmentAll computational analyses were implemented in R (version 4.5.2).

Key dependent packages include DESeq2, cluster, kernlab, and ggplot2.Intended useThis dataset supports full reproducibility of all computational analyses and figures in the corresponding manuscript. It also provides a reference analytical pipeline for exploring host-virus interaction associated molecular subtypes in other vasculitis or autoimmune disease studies.