Statistical analysis
REGRESSION
Data analysis was performed using GraphPad Prism (v9.2.0) and RStudio (v1.3 and R v4.0). Prior to analysis, all data were normalized using z-scoring. Statistical comparisons between groups were performed using Mann-Whitney Multivariate classification models were built to discriminate humoral profiles between treatment groups on day 15. Feature selection was performed using a least absolute shrinkage and selection operator (LASSO). Classification and visualization were performed using PLS-R, and model accuracy was assessed using 10-fold cross-validation. In each run, samples were stratified into training and test subsets; for each test fold, LASSO-based feature selection was performed on logistic regression using the nine subsets designated as the training set for that fold. LASSO was repeated 100 times; features selected ≥90 times out of 100 were identified as selected features. PLS-R was applied to the training set using the selected features, and prediction accuracy was recorded. Selected features were ordered according to variable importance in the projection score, and the first two latent variables of the PLS-R model were used to visualize the samples. These analyses were performed using the R package “ropls” version 1.20.0 (