Last updated: 2024-11-25

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Infant AP vs. WP visit:vaccinated - vaccinated : PCA Results

Antigen: PT

Features: PT_ADCD, PT_ADCP, PT_ADNP, PT_FcgR2a, PT_FcgR3b, PT_IgG1, PT_IgG2, PT_IgG4, PT_IgG3

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.983 1.287 0.921 0.806 0.756
Proportion of Variance 0.437 0.184 0.094 0.072 0.064
Cumulative Proportion 0.437 0.621 0.715 0.787 0.851

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated PT PC1: p=.14
Infant AP vs. WP vaccinated PT PC2: p<.0001

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated PT UMAP1: p<.0001
Infant AP vs. WP vaccinated PT UMAP2: p=.035

Antigen: FHA

Features: FHA_ADCD, FHA_ADCP, FHA_ADNP, FHA_IgG1, FHA_IgG2, FHA_IgG4, FHA_IgG3, FHA_FcgR2a, FHA_FcgR3b

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.835 1.265 1.099 0.903 0.843
Proportion of Variance 0.374 0.178 0.134 0.091 0.079
Cumulative Proportion 0.374 0.552 0.686 0.777 0.856

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated FHA PC1: p=.23
Infant AP vs. WP vaccinated FHA PC2: p<.0001

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated FHA UMAP1: p<.0001
Infant AP vs. WP vaccinated FHA UMAP2: p<.0001

Antigen: PRN

Features: PRN_ADCD, PRN_ADNP, PRN_ADCP, PRN_IgG1, PRN_IgG2, PRN_IgG4, PRN_IgG3, PRN_FcgR2a, PRN_FcgR3b

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.599 1.292 1.059 0.984 0.903
Proportion of Variance 0.284 0.186 0.125 0.108 0.091
Cumulative Proportion 0.284 0.470 0.594 0.702 0.793

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated PRN PC1: p=.52
Infant AP vs. WP vaccinated PRN PC2: p=.00013

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated PRN UMAP1: p=.22
Infant AP vs. WP vaccinated PRN UMAP2: p<.0001

Antigen: DT

Features: DT_ADCD, DT_ADCP, DT_ADNP, DT_FcgR2a, DT_FcgR3b, DT_IgG1, DT_IgG2, DT_IgG4, DT_IgG3

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.639 1.262 1.231 0.971 0.877
Proportion of Variance 0.298 0.177 0.168 0.105 0.086
Cumulative Proportion 0.298 0.475 0.644 0.748 0.834

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated DT PC1: p=.11
Infant AP vs. WP vaccinated DT PC2: p<.0001

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated DT UMAP1: p<.0001
Infant AP vs. WP vaccinated DT UMAP2: p<.0001

Antigen: TT

Features: TT_ADCD, TT_FcgR2a, TT_IgG1, TT_IgG2, TT_IgG4, TT_IgG3, TT_ADCP, TT_ADNP, TT_FcgR3b

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.954 1.261 0.961 0.866 0.723
Proportion of Variance 0.424 0.177 0.103 0.083 0.058
Cumulative Proportion 0.424 0.601 0.704 0.787 0.845

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated TT PC1: p=.02
Infant AP vs. WP vaccinated TT PC2: p<.0001

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated TT UMAP1: p<.0001
Infant AP vs. WP vaccinated TT UMAP2: p<.0001

Feature Cluster: IgG2 / IgG4

Features: DT_IgG2, DT_IgG4, FHA_IgG2, FHA_IgG4, PRN_IgG2, PRN_IgG4, PT_IgG2, PT_IgG4, TT_IgG2, TT_IgG4

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
Standard deviation 2.291 1.016 0.961 0.868 0.724 0.677 0.602 0.545 0.453 0.441
Proportion of Variance 0.525 0.103 0.092 0.075 0.052 0.046 0.036 0.030 0.021 0.019
Cumulative Proportion 0.525 0.628 0.721 0.796 0.848 0.894 0.930 0.960 0.981 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated Feature Cluster IgG2 / IgG4 PC1: p<.0001
Infant AP vs. WP vaccinated Feature Cluster IgG2 / IgG4 PC2: p=.063

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated TT UMAP1: p=.68
Infant AP vs. WP vaccinated TT UMAP2: p<.0001

Feature Cluster: ADCD

Features: DT_ADCD, FHA_ADCD, PRN_ADCD, TT_ADCD, PT_ADCD

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.858 0.810 0.738 0.471 0.356
Proportion of Variance 0.690 0.131 0.109 0.044 0.025
Cumulative Proportion 0.690 0.821 0.930 0.975 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated Feature Cluster ADCD PC1: p=.77
Infant AP vs. WP vaccinated Feature Cluster ADCD PC2: p=.37

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated TT UMAP1: p=.27
Infant AP vs. WP vaccinated TT UMAP2: p=.47

Feature Cluster: ADNP / ADCP

Features: DT_ADCP, PRN_ADNP, DT_ADNP, FHA_ADCP, FHA_ADNP, PRN_ADCP, PT_ADCP, PT_ADNP, TT_ADCP, TT_ADNP

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
Standard deviation 1.691 1.371 1.093 1.027 0.864 0.765 0.753 0.708 0.567 0.542
Proportion of Variance 0.286 0.188 0.119 0.105 0.075 0.058 0.057 0.050 0.032 0.029
Cumulative Proportion 0.286 0.474 0.593 0.699 0.773 0.832 0.888 0.938 0.971 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated Feature Cluster ADNP / ADCP PC1: p=.007
Infant AP vs. WP vaccinated Feature Cluster ADNP / ADCP PC2: p=.72

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated TT UMAP1: p=.057
Infant AP vs. WP vaccinated TT UMAP2: p=.0035

Feature Cluster: FcgR2a / FcgR3b

Features: DT_FcgR2a, DT_FcgR3b, PT_FcgR2a, PT_FcgR3b, TT_FcgR2a, FHA_FcgR2a, FHA_FcgR3b, PRN_FcgR2a, PRN_FcgR3b, TT_FcgR3b

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
Standard deviation 2.483 1.134 0.865 0.786 0.680 0.580 0.406 0.306 0.268 0.229
Proportion of Variance 0.617 0.128 0.075 0.062 0.046 0.034 0.016 0.009 0.007 0.005
Cumulative Proportion 0.617 0.745 0.820 0.882 0.928 0.962 0.978 0.988 0.995 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated Feature Cluster FcgR2a / FcgR3b PC1: p=.85
Infant AP vs. WP vaccinated Feature Cluster FcgR2a / FcgR3b PC2: p=.79

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated TT UMAP1: p=.79
Infant AP vs. WP vaccinated TT UMAP2: p=.81

Feature Cluster: IgG1

Features: PT_IgG1, DT_IgG1, FHA_IgG1, PRN_IgG1, TT_IgG1

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.696 0.907 0.782 0.673 0.488
Proportion of Variance 0.575 0.165 0.122 0.091 0.048
Cumulative Proportion 0.575 0.740 0.862 0.952 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated Feature Cluster IgG1 PC1: p=.73
Infant AP vs. WP vaccinated Feature Cluster IgG1 PC2: p=.87

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated TT UMAP1: p=.27
Infant AP vs. WP vaccinated TT UMAP2: p=.77

Feature Cluster: IgG3

Features: DT_IgG3, FHA_IgG3, PRN_IgG3, PT_IgG3, TT_IgG3

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.735 0.808 0.755 0.624 0.613
Proportion of Variance 0.602 0.131 0.114 0.078 0.075
Cumulative Proportion 0.602 0.733 0.847 0.925 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated Feature Cluster IgG3 PC1: p=.28
Infant AP vs. WP vaccinated Feature Cluster IgG3 PC2: p=.28

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated TT UMAP1: p=.24
Infant AP vs. WP vaccinated TT UMAP2: p=.43

Feature Cluster: IgG

Features:

Response Cluster: 1

Features: DT_ADCD, DT_ADCP, FHA_ADCD, PRN_ADCD, PRN_ADNP, TT_ADCD

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6
Standard deviation 1.764 1.016 0.972 0.730 0.505 0.354
Proportion of Variance 0.518 0.172 0.158 0.089 0.042 0.021
Cumulative Proportion 0.518 0.690 0.848 0.937 0.979 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated RCluster_ 1 PC1: p=.98
Infant AP vs. WP vaccinated RCluster_ 1 PC2: p=.65

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated TT UMAP1: p=.42
Infant AP vs. WP vaccinated TT UMAP2: p=.82

Response Cluster: 2

Features: DT_ADNP, FHA_ADCP, FHA_ADNP, PRN_ADCP

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4
Standard deviation 1.435 0.917 0.790 0.690
Proportion of Variance 0.514 0.210 0.156 0.119
Cumulative Proportion 0.514 0.725 0.881 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated RCluster_ 2 PC1: p=.031
Infant AP vs. WP vaccinated RCluster_ 2 PC2: p=.6

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated TT UMAP1: p=.75
Infant AP vs. WP vaccinated TT UMAP2: p=.063

Response Cluster: 3

Features: DT_FcgR2a, DT_FcgR3b, PT_ADCD, PT_ADCP, PT_ADNP, PT_FcgR2a, PT_FcgR3b, PT_IgG1, TT_FcgR2a

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9
Standard deviation 2.257 1.008 0.863 0.781 0.760 0.680 0.586 0.307 0.236
Proportion of Variance 0.566 0.113 0.083 0.068 0.064 0.051 0.038 0.010 0.006
Cumulative Proportion 0.566 0.679 0.762 0.830 0.894 0.945 0.983 0.994 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated RCluster_ 3 PC1: p=.63
Infant AP vs. WP vaccinated RCluster_ 3 PC2: p=.68

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated TT UMAP1: p=.011
Infant AP vs. WP vaccinated TT UMAP2: p=.77

Response Cluster: 4

Features: DT_IgG1, FHA_IgG1, PRN_IgG1, TT_IgG1

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4
Standard deviation 1.589 0.818 0.729 0.526
Proportion of Variance 0.631 0.167 0.133 0.069
Cumulative Proportion 0.631 0.798 0.931 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated RCluster_ 4 PC1: p=.81
Infant AP vs. WP vaccinated RCluster_ 4 PC2: p=.021

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated TT UMAP1: p=.74
Infant AP vs. WP vaccinated TT UMAP2: p=.31

Response Cluster: 5

Features: DT_IgG2, DT_IgG4, FHA_IgG2, FHA_IgG4, PRN_IgG2, PRN_IgG4, PT_IgG2, PT_IgG4, TT_IgG2, TT_IgG4

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
Standard deviation 2.291 1.016 0.961 0.868 0.724 0.677 0.602 0.545 0.453 0.441
Proportion of Variance 0.525 0.103 0.092 0.075 0.052 0.046 0.036 0.030 0.021 0.019
Cumulative Proportion 0.525 0.628 0.721 0.796 0.848 0.894 0.930 0.960 0.981 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated RCluster_ 5 PC1: p<.0001
Infant AP vs. WP vaccinated RCluster_ 5 PC2: p=.063

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated TT UMAP1: p=.68
Infant AP vs. WP vaccinated TT UMAP2: p<.0001

Response Cluster: 6

Features: DT_IgG3, FHA_IgG3, PRN_IgG3, PT_IgG3, TT_IgG3

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.735 0.808 0.755 0.624 0.613
Proportion of Variance 0.602 0.131 0.114 0.078 0.075
Cumulative Proportion 0.602 0.733 0.847 0.925 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated RCluster_ 6 PC1: p=.28
Infant AP vs. WP vaccinated RCluster_ 6 PC2: p=.28

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated TT UMAP1: p=.24
Infant AP vs. WP vaccinated TT UMAP2: p=.43

Response Cluster: 7

Features: FHA_FcgR2a, FHA_FcgR3b, PRN_FcgR2a, PRN_FcgR3b, TT_ADCP, TT_ADNP, TT_FcgR3b

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7
Standard deviation 2.055 1.004 0.841 0.657 0.562 0.459 0.324
Proportion of Variance 0.603 0.144 0.101 0.062 0.045 0.030 0.015
Cumulative Proportion 0.603 0.747 0.848 0.910 0.955 0.985 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP vaccinated RCluster_ 7 PC1: p=.31
Infant AP vs. WP vaccinated RCluster_ 7 PC2: p=.0031

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP vaccinated TT UMAP1: p=.0083
Infant AP vs. WP vaccinated TT UMAP2: p=.22

Infant AP vs. WP visit: boosted - boosted : PCA Results

Antigen: PT

Features: PT_ADCD, PT_IgG1, PT_ADNP, PT_IgG3, PT_IgG2, PT_IgG4, PT_ADCP, PT_FcgR2a, PT_FcgR3b

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.797 1.353 1.038 0.919 0.827
Proportion of Variance 0.359 0.203 0.120 0.094 0.076
Cumulative Proportion 0.359 0.562 0.682 0.776 0.852

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted PT PC1: p=.00053
Infant AP vs. WP boosted PT PC2: p<.0001

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted PT UMAP1: p<.0001
Infant AP vs. WP boosted PT UMAP2: p<.0001

Antigen: FHA

Features: FHA_ADCD, FHA_IgG1, FHA_IgG2, FHA_IgG4, FHA_IgG3, FHA_ADCP, FHA_ADNP, FHA_FcgR2a, FHA_FcgR3b

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.876 1.182 1.085 0.912 0.849
Proportion of Variance 0.391 0.155 0.131 0.092 0.080
Cumulative Proportion 0.391 0.546 0.677 0.770 0.850

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted FHA PC1: p=.00042
Infant AP vs. WP boosted FHA PC2: p=.00064

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted FHA UMAP1: p<.0001
Infant AP vs. WP boosted FHA UMAP2: p=.33

Antigen: PRN

Features: PRN_ADCD, PRN_IgG1, PRN_ADNP, PRN_IgG2, PRN_IgG4, PRN_IgG3, PRN_ADCP, PRN_FcgR2a, PRN_FcgR3b

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.562 1.384 1.100 1.014 0.943
Proportion of Variance 0.271 0.213 0.134 0.114 0.099
Cumulative Proportion 0.271 0.484 0.619 0.733 0.832

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted PRN PC1: p=.68
Infant AP vs. WP boosted PRN PC2: p<.0001

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted PRN UMAP1: p<.0001
Infant AP vs. WP boosted PRN UMAP2: p<.0001

Antigen: DT

Features: DT_ADCD, DT_ADCP, DT_ADNP, DT_IgG1, DT_FcgR2a, DT_FcgR3b, DT_IgG4, DT_IgG2, DT_IgG3

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.436 1.259 1.162 1.123 1.041
Proportion of Variance 0.229 0.176 0.150 0.140 0.120
Cumulative Proportion 0.229 0.405 0.555 0.695 0.816

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted DT PC1: p=.66
Infant AP vs. WP boosted DT PC2: p=.0002

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted DT UMAP1: p=.15
Infant AP vs. WP boosted DT UMAP2: p=.00077

Antigen: TT

Features: TT_ADCD, TT_FcgR2a, TT_IgG1, TT_ADNP, TT_IgG2, TT_IgG4, TT_IgG3, TT_ADCP, TT_FcgR3b

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.706 1.175 1.130 0.946 0.926
Proportion of Variance 0.323 0.153 0.142 0.099 0.095
Cumulative Proportion 0.323 0.477 0.619 0.718 0.813

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted TT PC1: p<.0001
Infant AP vs. WP boosted TT PC2: p=.029

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted TT UMAP1: p=.0003
Infant AP vs. WP boosted TT UMAP2: p<.0001

Feature Cluster: IgG2 / IgG4

Features: DT_IgG4, DT_IgG2, FHA_IgG2, FHA_IgG4, PRN_IgG2, PRN_IgG4, PT_IgG2, PT_IgG4, TT_IgG2, TT_IgG4

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
Standard deviation 2.350 0.979 0.967 0.847 0.781 0.715 0.558 0.405 0.395 0.336
Proportion of Variance 0.552 0.096 0.093 0.072 0.061 0.051 0.031 0.016 0.016 0.011
Cumulative Proportion 0.552 0.648 0.742 0.813 0.874 0.926 0.957 0.973 0.989 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted Feature Cluster IgG2 / IgG4 PC1: p<.0001
Infant AP vs. WP boosted Feature Cluster IgG2 / IgG4 PC2: p=.53

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted TT UMAP1: p<.0001
Infant AP vs. WP boosted TT UMAP2: p<.0001

Feature Cluster: ADCD

Features: DT_ADCD, FHA_ADCD, PRN_ADCD, PT_ADCD, TT_ADCD

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.899 0.728 0.602 0.558 0.433
Proportion of Variance 0.722 0.106 0.073 0.062 0.038
Cumulative Proportion 0.722 0.828 0.900 0.962 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted Feature Cluster ADCD PC1: p=.99
Infant AP vs. WP boosted Feature Cluster ADCD PC2: p=.0018

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted TT UMAP1: p=.54
Infant AP vs. WP boosted TT UMAP2: p=.7

Feature Cluster: ADNP / ADCP

Features: DT_ADCP, DT_ADNP, PRN_ADNP, PT_ADNP, TT_ADNP, FHA_ADCP, PRN_ADCP, TT_ADCP, FHA_ADNP, PT_ADCP

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
Standard deviation 1.717 1.404 1.195 0.963 0.851 0.780 0.705 0.625 0.544 0.458
Proportion of Variance 0.295 0.197 0.143 0.093 0.072 0.061 0.050 0.039 0.030 0.021
Cumulative Proportion 0.295 0.492 0.635 0.728 0.800 0.861 0.910 0.949 0.979 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted Feature Cluster ADNP / ADCP PC1: p=.14
Infant AP vs. WP boosted Feature Cluster ADNP / ADCP PC2: p=.099

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted TT UMAP1: p=.39
Infant AP vs. WP boosted TT UMAP2: p=.91

Feature Cluster: FcgR2a / FcgR3b

Features: TT_FcgR2a, DT_FcgR2a, DT_FcgR3b, FHA_FcgR2a, FHA_FcgR3b, PRN_FcgR2a, PRN_FcgR3b, PT_FcgR2a, PT_FcgR3b, TT_FcgR3b

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
Standard deviation 2.136 1.283 1.087 0.966 0.843 0.716 0.436 0.373 0.290 0.197
Proportion of Variance 0.456 0.165 0.118 0.093 0.071 0.051 0.019 0.014 0.008 0.004
Cumulative Proportion 0.456 0.621 0.739 0.832 0.904 0.955 0.974 0.988 0.996 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted Feature Cluster FcgR2a / FcgR3b PC1: p=.41
Infant AP vs. WP boosted Feature Cluster FcgR2a / FcgR3b PC2: p=.0046

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted TT UMAP1: p=.12
Infant AP vs. WP boosted TT UMAP2: p=.096

Feature Cluster: IgG1

Features: DT_IgG1, FHA_IgG1, PRN_IgG1, PT_IgG1, TT_IgG1

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.669 0.862 0.747 0.705 0.646
Proportion of Variance 0.557 0.149 0.112 0.099 0.084
Cumulative Proportion 0.557 0.706 0.817 0.916 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted Feature Cluster IgG1 PC1: p=.71
Infant AP vs. WP boosted Feature Cluster IgG1 PC2: p=.61

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted TT UMAP1: p=.86
Infant AP vs. WP boosted TT UMAP2: p=.36

Feature Cluster: IgG3

Features: PT_IgG3, DT_IgG3, FHA_IgG3, PRN_IgG3, TT_IgG3

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.533 0.945 0.814 0.764 0.714
Proportion of Variance 0.470 0.178 0.133 0.117 0.102
Cumulative Proportion 0.470 0.649 0.781 0.898 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted Feature Cluster IgG3 PC1: p=.21
Infant AP vs. WP boosted Feature Cluster IgG3 PC2: p=1

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted TT UMAP1: p=.13
Infant AP vs. WP boosted TT UMAP2: p=.25

Feature Cluster: IgG

Features:

Response Cluster: 1

Features: DT_ADCD, FHA_ADCD, PRN_ADCD, PT_ADCD, TT_ADCD, TT_FcgR2a

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6
Standard deviation 1.973 0.879 0.720 0.598 0.539 0.410
Proportion of Variance 0.649 0.129 0.086 0.060 0.048 0.028
Cumulative Proportion 0.649 0.778 0.864 0.924 0.972 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted RCluster_ 1 PC1: p=.84
Infant AP vs. WP boosted RCluster_ 1 PC2: p=.26

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted TT UMAP1: p=.96
Infant AP vs. WP boosted TT UMAP2: p=.63

Response Cluster: 2

Features: DT_ADCP, DT_ADNP, DT_IgG1, FHA_IgG1, PRN_IgG1, PT_IgG1, TT_IgG1

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7
Standard deviation 1.702 1.152 0.884 0.785 0.730 0.677 0.624
Proportion of Variance 0.414 0.189 0.112 0.088 0.076 0.065 0.056
Cumulative Proportion 0.414 0.603 0.715 0.803 0.879 0.944 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted RCluster_ 2 PC1: p=.52
Infant AP vs. WP boosted RCluster_ 2 PC2: p=.11

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted TT UMAP1: p=.74
Infant AP vs. WP boosted TT UMAP2: p=.92

Response Cluster: 3

Features: DT_FcgR2a, DT_FcgR3b, DT_IgG4, PRN_ADNP, PT_ADNP, PT_IgG3, TT_ADNP

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7
Standard deviation 1.482 1.233 1.102 0.908 0.723 0.689 0.495
Proportion of Variance 0.314 0.217 0.173 0.118 0.075 0.068 0.035
Cumulative Proportion 0.314 0.531 0.705 0.822 0.897 0.965 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted RCluster_ 3 PC1: p=.22
Infant AP vs. WP boosted RCluster_ 3 PC2: p=.095

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted TT UMAP1: p=.053
Infant AP vs. WP boosted TT UMAP2: p=.014

Response Cluster: 4

Features: DT_IgG2, FHA_IgG2, FHA_IgG4, PRN_IgG2, PRN_IgG4, PT_IgG2, PT_IgG4, TT_IgG2, TT_IgG4

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9
Standard deviation 2.307 0.968 0.849 0.781 0.719 0.643 0.435 0.400 0.363
Proportion of Variance 0.591 0.104 0.080 0.068 0.057 0.046 0.021 0.018 0.015
Cumulative Proportion 0.591 0.695 0.775 0.843 0.901 0.947 0.968 0.985 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted RCluster_ 4 PC1: p<.0001
Infant AP vs. WP boosted RCluster_ 4 PC2: p=.83

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted TT UMAP1: p<.0001
Infant AP vs. WP boosted TT UMAP2: p<.0001

Response Cluster: 5

Features: DT_IgG3, FHA_IgG3, PRN_IgG3, TT_IgG3

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4
Standard deviation 1.487 0.820 0.766 0.729
Proportion of Variance 0.553 0.168 0.147 0.133
Cumulative Proportion 0.553 0.721 0.867 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted RCluster_ 5 PC1: p=.21
Infant AP vs. WP boosted RCluster_ 5 PC2: p=.076

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted TT UMAP1: p=.16
Infant AP vs. WP boosted TT UMAP2: p=.83

Response Cluster: 6

Features: FHA_ADCP, PRN_ADCP, TT_ADCP

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3
Standard deviation 1.405 0.765 0.663
Proportion of Variance 0.658 0.195 0.147
Cumulative Proportion 0.658 0.853 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted RCluster_ 6 PC1: p=.059
Infant AP vs. WP boosted RCluster_ 6 PC2: p=.79

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted TT UMAP1: p=.075
Infant AP vs. WP boosted TT UMAP2: p=.63

Response Cluster: 7

Features: FHA_ADNP, FHA_FcgR2a, FHA_FcgR3b, PRN_FcgR2a, PRN_FcgR3b, PT_ADCP, PT_FcgR2a, PT_FcgR3b, TT_FcgR3b

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9
Standard deviation 2.159 1.202 0.974 0.840 0.808 0.526 0.431 0.281 0.209
Proportion of Variance 0.518 0.160 0.105 0.078 0.073 0.031 0.021 0.009 0.005
Cumulative Proportion 0.518 0.679 0.784 0.862 0.935 0.966 0.986 0.995 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Infant AP vs. WP boosted RCluster_ 7 PC1: p=.58
Infant AP vs. WP boosted RCluster_ 7 PC2: p=.00014

Plot of PCA Eigen Vectors

Correlation between features and each PC score - colored by variance contribution

**Loadings plot

Plot of UMAP1 vs UMAP2 Loadings

Comparison of UMAP loadings by arm
Infant AP vs. WP boosted TT UMAP1: p=.059
Infant AP vs. WP boosted TT UMAP2: p=.12


sessionInfo()
R version 4.4.2 (2024-10-31)
Platform: aarch64-apple-darwin20
Running under: macOS Sequoia 15.1.1

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRblas.0.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: America/New_York
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] e1071_1.7-16         glue_1.8.0           RPostgres_1.4.7     
 [4] magrittr_2.0.3       broom.helpers_1.17.0 broom_1.0.7         
 [7] RColorBrewer_1.1-3   skimr_2.1.5          rmarkdown_2.28      
[10] papeR_1.0-5          xtable_1.8-4         car_3.1-3           
[13] carData_3.0-5        corrplot_0.94        rempsyc_0.1.8       
[16] FactoMineR_2.11      factoextra_1.0.7     rstatix_0.7.2       
[19] umap_0.2.10.0        pracma_2.4.4         PCAmixdata_3.1      
[22] qgraph_1.9.8         kableExtra_1.4.0     gtsummary_2.0.3     
[25] gtExtras_0.5.0       gt_0.11.1            ggfortify_0.4.17    
[28] ggpubr_0.6.0         ggExtra_0.10.1       ggrepel_0.9.6       
[31] janitor_2.2.0        here_1.0.1           data.table_1.16.2   
[34] DT_0.33              DBI_1.2.3            fpc_2.2-13          
[37] lubridate_1.9.3      forcats_1.0.0        stringr_1.5.1       
[40] dplyr_1.1.4          purrr_1.0.2          readr_2.1.5         
[43] tidyr_1.3.1          tibble_3.2.1         ggplot2_3.5.1       
[46] tidyverse_2.0.0     

loaded via a namespace (and not attached):
  [1] splines_4.4.2        later_1.3.2          rpart_4.1.23        
  [4] lifecycle_1.0.4      rprojroot_2.0.4      lattice_0.22-6      
  [7] prabclus_2.3-4       MASS_7.3-61          flashClust_1.01-2   
 [10] backports_1.5.0      Hmisc_5.1-3          sass_0.4.9          
 [13] jquerylib_0.1.4      yaml_2.3.10          httpuv_1.6.15       
 [16] flexmix_2.3-19       askpass_1.2.1        reticulate_1.39.0   
 [19] pbapply_1.7-2        multcomp_1.4-26      abind_1.4-8         
 [22] quadprog_1.5-8       TH.data_1.1-2        nnet_7.3-19         
 [25] sandwich_3.1-1       git2r_0.33.0         gmodels_2.19.1      
 [28] gdata_3.0.0          RSpectra_0.16-2      svglite_2.1.3       
 [31] codetools_0.2-20     xml2_1.3.6           tidyselect_1.2.1    
 [34] farver_2.1.2         stats4_4.4.2         base64enc_0.1-3     
 [37] jsonlite_1.8.9       Formula_1.2-5        survival_3.7-0      
 [40] emmeans_1.10.4       systemfonts_1.1.0    tools_4.4.2         
 [43] Rcpp_1.0.13          mnormt_2.1.1         gridExtra_2.3       
 [46] xfun_0.48            withr_3.0.1          fastmap_1.2.0       
 [49] fansi_1.0.6          openssl_2.2.2        digest_0.6.37       
 [52] timechange_0.3.0     R6_2.5.1             mime_0.12           
 [55] estimability_1.5.1   colorspace_2.1-1     gtools_3.9.5        
 [58] jpeg_0.1-10          diptest_0.77-1       utf8_1.2.4          
 [61] generics_0.1.3       corpcor_1.6.10       robustbase_0.99-4-1 
 [64] class_7.3-22         htmlwidgets_1.6.4    scatterplot3d_0.3-44
 [67] whisker_0.4.1        pkgconfig_2.0.3      gtable_0.3.5        
 [70] modeltools_0.2-23    blob_1.2.4           workflowr_1.7.1     
 [73] htmltools_0.5.8.1    lavaan_0.6-19        multcompView_0.1-10 
 [76] scales_1.3.0         leaps_3.2            png_0.1-8           
 [79] snakecase_0.11.1     knitr_1.48.1         rstudioapi_0.16.0   
 [82] tzdb_0.4.0           reshape2_1.4.4       coda_0.19-4.1       
 [85] checkmate_2.3.2      nlme_3.1-166         proxy_0.4-27        
 [88] repr_1.1.7           zoo_1.8-12           cachem_1.1.0        
 [91] parallel_4.4.2       miniUI_0.1.1.1       foreign_0.8-87      
 [94] pillar_1.9.0         grid_4.4.2           vctrs_0.6.5         
 [97] promises_1.3.0       cluster_2.1.6        htmlTable_2.4.3     
[100] paletteer_1.6.0      evaluate_1.0.1       pbivnorm_0.6.0      
[103] mvtnorm_1.3-1        cli_3.6.3            compiler_4.4.2      
[106] rlang_1.1.4          ggsignif_0.6.4       labeling_0.4.3      
[109] fdrtool_1.2.18       mclust_6.1.1         rematch2_2.1.2      
[112] plyr_1.8.9           fs_1.6.4             stringi_1.8.4       
[115] psych_2.4.6.26       viridisLite_0.4.2    munsell_0.5.1       
[118] Matrix_1.7-1         hms_1.1.3            glasso_1.11         
[121] bit64_4.5.2          shiny_1.9.1          highr_0.11          
[124] kernlab_0.9-33       fontawesome_0.5.2    igraph_2.0.3        
[127] bslib_0.8.0          bit_4.5.0            DEoptimR_1.1-3