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Assignment4
Assignment 4 k-fold cross validation | bootstrapping
Final Report_W
data 110
Clustering of Cytokines
What This Analysis Does: 1) Data preparation — generates a simulated cytokine dataset (Control vs. 2) Sepsis groups) with 5 analytes: IL-6, TNF-α, IL-10, IFN-γ, and IL-1β. These are major inflammatory cytokines indicative of sepsis in murine species. Each cytokine concentration was generated via a form of a random normal distribution. 3) Preprocessing — removes non-numeric columns, checks for missing values, and z-score scales the data 4) PCA — runs principal component analysis, produces a scree plot, PC1/PC2 biplot with 95% confidence ellipses, and a PC1 loadings plot 5) Hierarchical clustering — builds a distance matrix, plots a color-labeled dendrogram, and evaluates cluster-to-group concordance 6) K-means clustering — fits a 2-center k-means model and overlays cluster assignments on the PCA plot 7) Heatmap visualization — generates annotated heatmaps using base R and pheatmap, with group color annotations to further characterize clusters and sepsis profiles.