Last updated: 2024-12-02

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Maternal Tdap+ vs. Tdap- visit:vaccinated - vaccinated : PCA Results

Antigen: PT

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

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 2.424 1.116 0.942 0.858 0.657
Proportion of Variance 0.588 0.125 0.089 0.074 0.043
Cumulative Proportion 0.588 0.712 0.801 0.875 0.918

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated PT PC1: p=.38
Maternal Tdap+ vs. Tdap- vaccinated PT PC2: p=.0032

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
Maternal Tdap+ vs. Tdap- vaccinated PT UMAP1: p=.5
Maternal Tdap+ vs. Tdap- vaccinated PT UMAP2: p=.23

Antigen: FHA

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

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 2.260 1.210 0.986 0.781 0.722
Proportion of Variance 0.511 0.146 0.097 0.061 0.052
Cumulative Proportion 0.511 0.657 0.755 0.816 0.868

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated FHA PC1: p=.63
Maternal Tdap+ vs. Tdap- 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
Maternal Tdap+ vs. Tdap- vaccinated FHA UMAP1: p=.48
Maternal Tdap+ vs. Tdap- vaccinated FHA UMAP2: p=.64

Antigen: PRN

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

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 2.310 1.038 0.961 0.885 0.827
Proportion of Variance 0.534 0.108 0.092 0.078 0.068
Cumulative Proportion 0.534 0.642 0.734 0.812 0.881

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated PRN PC1: p=.34
Maternal Tdap+ vs. Tdap- vaccinated PRN PC2: p=.22

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
Maternal Tdap+ vs. Tdap- vaccinated PRN UMAP1: p=.28
Maternal Tdap+ vs. Tdap- vaccinated PRN UMAP2: p=.38

Antigen: DT

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

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.930 1.263 1.113 1.040 0.852
Proportion of Variance 0.372 0.159 0.124 0.108 0.073
Cumulative Proportion 0.372 0.532 0.656 0.764 0.836

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated DT PC1: p=.63
Maternal Tdap+ vs. Tdap- vaccinated DT PC2: p=.002

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
Maternal Tdap+ vs. Tdap- vaccinated DT UMAP1: p=.91
Maternal Tdap+ vs. Tdap- vaccinated DT UMAP2: p=.019

Antigen: TT

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

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 2.393 1.161 0.970 0.699 0.657
Proportion of Variance 0.572 0.135 0.094 0.049 0.043
Cumulative Proportion 0.572 0.707 0.801 0.850 0.894

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated TT PC1: p=.0017
Maternal Tdap+ vs. Tdap- vaccinated TT PC2: p=.66

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
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP1: p=.026
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP2: p=.0088

Feature Cluster: IgG2 / IgG4

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

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
Standard deviation 1.833 1.231 1.114 1.036 0.947 0.749 0.692 0.633 0.527 0.440
Proportion of Variance 0.336 0.152 0.124 0.107 0.090 0.056 0.048 0.040 0.028 0.019
Cumulative Proportion 0.336 0.488 0.612 0.719 0.809 0.865 0.913 0.953 0.981 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated Feature Cluster IgG2 / IgG4 PC1: p=.1
Maternal Tdap+ vs. Tdap- vaccinated Feature Cluster IgG2 / IgG4 PC2: p=.0065

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
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP1: p=.023
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP2: p=.056

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 1.851 0.881 0.672 0.459 0.367
Proportion of Variance 0.686 0.155 0.090 0.042 0.027
Cumulative Proportion 0.686 0.841 0.931 0.973 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated Feature Cluster ADCD PC1: p=.023
Maternal Tdap+ vs. Tdap- vaccinated Feature Cluster ADCD PC2: p=.94

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
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP1: p=.92
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP2: p=.7

Feature Cluster: ADNP / ADCP

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

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
Standard deviation 1.707 1.228 1.088 1.020 0.944 0.886 0.814 0.692 0.590 0.436
Proportion of Variance 0.291 0.151 0.118 0.104 0.089 0.078 0.066 0.048 0.035 0.019
Cumulative Proportion 0.291 0.442 0.561 0.665 0.754 0.832 0.898 0.946 0.981 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated Feature Cluster ADNP / ADCP PC1: p=.1
Maternal Tdap+ vs. Tdap- vaccinated Feature Cluster ADNP / ADCP 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
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP1: p=.19
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP2: p=.29

Feature Cluster: FcgR2a / FcgR3b

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

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
Standard deviation 2.451 1.279 0.951 0.826 0.679 0.402 0.241 0.226 0.158 0.116
Proportion of Variance 0.601 0.164 0.090 0.068 0.046 0.016 0.006 0.005 0.002 0.001
Cumulative Proportion 0.601 0.764 0.855 0.923 0.969 0.985 0.991 0.996 0.999 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated Feature Cluster FcgR2a / FcgR3b PC1: p=.03
Maternal Tdap+ vs. Tdap- vaccinated Feature Cluster FcgR2a / FcgR3b PC2: p=.047

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
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP1: p=.0063
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP2: p=.03

Feature Cluster: IgG1

Features: DT_IgG1, FHA_IgG1, PT_IgG1, PRN_IgG1, TT_IgG1

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.647 0.907 0.845 0.640 0.583
Proportion of Variance 0.543 0.164 0.143 0.082 0.068
Cumulative Proportion 0.543 0.707 0.850 0.932 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated Feature Cluster IgG1 PC1: p=.83
Maternal Tdap+ vs. Tdap- vaccinated Feature Cluster IgG1 PC2: p=.0012

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
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP1: p=.32
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP2: p=.36

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 1.853 0.742 0.657 0.627 0.438
Proportion of Variance 0.686 0.110 0.086 0.079 0.038
Cumulative Proportion 0.686 0.797 0.883 0.962 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated Feature Cluster IgG3 PC1: p=.043
Maternal Tdap+ vs. Tdap- vaccinated Feature Cluster IgG3 PC2: p=.17

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
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP1: p=.46
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP2: p=.11

Feature Cluster: IgG

Features: DT_IgG, PT_IgG, FHA_IgG, PRN_IgG, TT_IgG

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.640 0.962 0.797 0.660 0.559
Proportion of Variance 0.538 0.185 0.127 0.087 0.063
Cumulative Proportion 0.538 0.723 0.850 0.937 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated Feature Cluster IgG PC1: p=.0077
Maternal Tdap+ vs. Tdap- vaccinated Feature Cluster IgG PC2: p=.00011

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
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP1: p=.74
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP2: p<.0001

Response Cluster: 1

Features: DT_ADCD, DT_IgG, DT_IgG1, FHA_ADCD, FHA_ADNP, FHA_FcgR2a, FHA_FcgR3b, FHA_IgG1, PRN_ADCD, PRN_ADNP, TT_ADCD

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 PC11
Standard deviation 2.235 1.383 1.236 0.892 0.711 0.637 0.584 0.437 0.396 0.327 0.244
Proportion of Variance 0.454 0.174 0.139 0.072 0.046 0.037 0.031 0.017 0.014 0.010 0.005
Cumulative Proportion 0.454 0.628 0.767 0.839 0.885 0.922 0.953 0.971 0.985 0.995 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated RCluster_ 1 PC1: p=.13
Maternal Tdap+ vs. Tdap- vaccinated RCluster_ 1 PC2: p=.38

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
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP1: p=.14
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP2: p=.76

Response Cluster: 2

Features: PT_ADCD, PT_ADCP, PT_FcgR2a, PT_FcgR3b, PT_IgG, PT_IgG1

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6
Standard deviation 2.214 0.733 0.530 0.380 0.339 0.144
Proportion of Variance 0.817 0.090 0.047 0.024 0.019 0.003
Cumulative Proportion 0.817 0.907 0.953 0.977 0.997 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated RCluster_ 2 PC1: p=.14
Maternal Tdap+ vs. Tdap- vaccinated RCluster_ 2 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
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP1: p=.0079
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP2: p=.061

Response Cluster: 3

Features: DT_ADCP, DT_IgG2, FHA_ADCP, FHA_IgG, FHA_IgG2, TT_IgG2

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6
Standard deviation 1.45 1.242 0.975 0.809 0.669 0.553
Proportion of Variance 0.35 0.257 0.158 0.109 0.075 0.051
Cumulative Proportion 0.35 0.607 0.766 0.875 0.949 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated RCluster_ 3 PC1: p=.00014
Maternal Tdap+ vs. Tdap- 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
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP1: p=.00013
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP2: p=.023

Response Cluster: 4

Features: PRN_ADCP, PRN_FcgR2a, PRN_FcgR3b, PRN_IgG, PRN_IgG1, PRN_IgG2

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6
Standard deviation 2.066 0.861 0.758 0.466 0.383 0.232
Proportion of Variance 0.711 0.124 0.096 0.036 0.024 0.009
Cumulative Proportion 0.711 0.835 0.930 0.967 0.991 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated RCluster_ 4 PC1: p=.48
Maternal Tdap+ vs. Tdap- vaccinated RCluster_ 4 PC2: p=.97

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
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP1: p=.79
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP2: p=.25

Response Cluster: 5

Features: DT_FcgR2a, DT_FcgR3b, DT_IgG3, FHA_IgG3, PRN_IgG3, PT_ADNP, PT_IgG3, TT_ADCP, TT_ADNP, TT_FcgR2a, TT_FcgR3b, TT_IgG, TT_IgG1, TT_IgG3

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 PC11 PC12 PC13 PC14
Standard deviation 2.881 1.193 1.018 0.789 0.743 0.650 0.627 0.554 0.520 0.475 0.418 0.360 0.312 0.214
Proportion of Variance 0.593 0.102 0.074 0.044 0.039 0.030 0.028 0.022 0.019 0.016 0.012 0.009 0.007 0.003
Cumulative Proportion 0.593 0.695 0.769 0.813 0.852 0.883 0.911 0.933 0.952 0.968 0.981 0.990 0.997 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated RCluster_ 5 PC1: p=.0083
Maternal Tdap+ vs. Tdap- vaccinated RCluster_ 5 PC2: p=.4

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
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP1: p=.043
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP2: p=.085

Response Cluster: 6

Features: DT_ADNP, PT_IgG2

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2
Standard deviation 1.098 0.891
Proportion of Variance 0.603 0.397
Cumulative Proportion 0.603 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated RCluster_ 6 PC1: p=.66
Maternal Tdap+ vs. Tdap- vaccinated RCluster_ 6 PC2: p=.29

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
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP1: p=.95
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP2: p=.19

Response Cluster: 7

Features: DT_IgG4, FHA_IgG4, PRN_IgG4, PT_IgG4, TT_IgG4

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.637 0.969 0.811 0.710 0.467
Proportion of Variance 0.536 0.188 0.131 0.101 0.044
Cumulative Proportion 0.536 0.724 0.855 0.956 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- vaccinated RCluster_ 7 PC1: p=.2
Maternal Tdap+ vs. Tdap- vaccinated RCluster_ 7 PC2: p=.017

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
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP1: p=.092
Maternal Tdap+ vs. Tdap- vaccinated TT UMAP2: p=.21

Maternal Tdap+ vs. Tdap- visit: boosted - boosted : PCA Results

Antigen: PT

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

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 2.031 1.196 0.951 0.940 0.878
Proportion of Variance 0.412 0.143 0.091 0.088 0.077
Cumulative Proportion 0.412 0.555 0.646 0.734 0.811

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted PT PC1: p=.11
Maternal Tdap+ vs. Tdap- boosted PT PC2: p=.015

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
Maternal Tdap+ vs. Tdap- boosted PT UMAP1: p=.59
Maternal Tdap+ vs. Tdap- boosted PT UMAP2: p=.012

Antigen: FHA

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

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 2.239 1.085 1.023 0.917 0.746
Proportion of Variance 0.501 0.118 0.105 0.084 0.056
Cumulative Proportion 0.501 0.619 0.724 0.808 0.864

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted FHA PC1: p=.027
Maternal Tdap+ vs. Tdap- boosted FHA PC2: p=.99

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
Maternal Tdap+ vs. Tdap- boosted FHA UMAP1: p=.02
Maternal Tdap+ vs. Tdap- boosted FHA UMAP2: p=.24

Antigen: PRN

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

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 2.216 1.112 0.985 0.912 0.869
Proportion of Variance 0.491 0.124 0.097 0.083 0.076
Cumulative Proportion 0.491 0.615 0.712 0.795 0.871

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted PRN PC1: p=.63
Maternal Tdap+ vs. Tdap- boosted PRN PC2: p=.39

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
Maternal Tdap+ vs. Tdap- boosted PRN UMAP1: p=.38
Maternal Tdap+ vs. Tdap- boosted PRN UMAP2: p=.88

Antigen: DT

Features: DT_ADCD, DT_FcgR2a, DT_ADCP, DT_ADNP, DT_FcgR3b, DT_IgG, 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 1.763 1.235 1.110 1.068 0.959
Proportion of Variance 0.311 0.153 0.123 0.114 0.092
Cumulative Proportion 0.311 0.463 0.587 0.701 0.793

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted DT PC1: p=.28
Maternal Tdap+ vs. Tdap- boosted DT 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
Maternal Tdap+ vs. Tdap- boosted DT UMAP1: p=.17
Maternal Tdap+ vs. Tdap- boosted DT UMAP2: p=.39

Antigen: TT

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

Proportion of Variance

Summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.636 1.244 1.160 1.047 0.996
Proportion of Variance 0.268 0.155 0.134 0.110 0.099
Cumulative Proportion 0.268 0.422 0.557 0.666 0.766

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted TT PC1: p=.66
Maternal Tdap+ vs. Tdap- boosted TT 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
Maternal Tdap+ vs. Tdap- boosted TT UMAP1: p=.58
Maternal Tdap+ vs. Tdap- boosted TT UMAP2: p=.67

Feature Cluster: IgG2 / IgG4

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

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
Standard deviation 1.851 1.158 1.115 1.050 0.905 0.895 0.654 0.560 0.526 0.501
Proportion of Variance 0.342 0.134 0.124 0.110 0.082 0.080 0.043 0.031 0.028 0.025
Cumulative Proportion 0.342 0.477 0.601 0.711 0.793 0.873 0.916 0.947 0.975 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted Feature Cluster IgG2 / IgG4 PC1: p=.71
Maternal Tdap+ vs. Tdap- boosted Feature Cluster IgG2 / IgG4 PC2: p=.03

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
Maternal Tdap+ vs. Tdap- boosted TT UMAP1: p=.45
Maternal Tdap+ vs. Tdap- boosted TT UMAP2: p=.31

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 1.874 0.807 0.616 0.604 0.303
Proportion of Variance 0.703 0.130 0.076 0.073 0.018
Cumulative Proportion 0.703 0.833 0.909 0.982 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted Feature Cluster ADCD PC1: p=.27
Maternal Tdap+ vs. Tdap- boosted 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
Maternal Tdap+ vs. Tdap- boosted TT UMAP1: p=.43
Maternal Tdap+ vs. Tdap- boosted TT UMAP2: p=.16

Feature Cluster: ADNP / ADCP

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

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
Standard deviation 1.772 1.278 1.079 1.002 0.920 0.859 0.771 0.700 0.471 0.414
Proportion of Variance 0.314 0.163 0.116 0.100 0.085 0.074 0.059 0.049 0.022 0.017
Cumulative Proportion 0.314 0.477 0.594 0.694 0.779 0.852 0.912 0.961 0.983 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted Feature Cluster ADNP / ADCP PC1: p=.84
Maternal Tdap+ vs. Tdap- boosted Feature Cluster ADNP / ADCP PC2: p=.63

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
Maternal Tdap+ vs. Tdap- boosted TT UMAP1: p=.77
Maternal Tdap+ vs. Tdap- boosted TT UMAP2: p=.21

Feature Cluster: FcgR2a / FcgR3b

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

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
Standard deviation 1.976 1.414 1.239 0.999 0.854 0.756 0.369 0.269 0.181 0.146
Proportion of Variance 0.390 0.200 0.153 0.100 0.073 0.057 0.014 0.007 0.003 0.002
Cumulative Proportion 0.390 0.590 0.744 0.844 0.917 0.974 0.987 0.995 0.998 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted Feature Cluster FcgR2a / FcgR3b PC1: p=.58
Maternal Tdap+ vs. Tdap- boosted Feature Cluster FcgR2a / FcgR3b 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
Maternal Tdap+ vs. Tdap- boosted TT UMAP1: p=.022
Maternal Tdap+ vs. Tdap- boosted TT UMAP2: p=.16

Feature Cluster: IgG1

Features: FHA_IgG1, PRN_IgG1, PT_IgG1, DT_IgG1, TT_IgG1

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.683 0.866 0.747 0.715 0.591
Proportion of Variance 0.566 0.150 0.112 0.102 0.070
Cumulative Proportion 0.566 0.716 0.828 0.930 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted Feature Cluster IgG1 PC1: p=.079
Maternal Tdap+ vs. Tdap- boosted Feature Cluster IgG1 PC2: p=.0049

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
Maternal Tdap+ vs. Tdap- boosted TT UMAP1: p=.38
Maternal Tdap+ vs. Tdap- boosted TT UMAP2: p=.12

Feature Cluster: IgG3

Features: PRN_IgG3, DT_IgG3, FHA_IgG3, PT_IgG3, TT_IgG3

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.617 0.859 0.787 0.749 0.684
Proportion of Variance 0.523 0.148 0.124 0.112 0.094
Cumulative Proportion 0.523 0.670 0.794 0.906 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted Feature Cluster IgG3 PC1: p=.31
Maternal Tdap+ vs. Tdap- boosted Feature Cluster IgG3 PC2: p=.59

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
Maternal Tdap+ vs. Tdap- boosted TT UMAP1: p=.64
Maternal Tdap+ vs. Tdap- boosted TT UMAP2: p=.36

Feature Cluster: IgG

Features: FHA_IgG, PRN_IgG, PT_IgG, DT_IgG, TT_IgG

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5
Standard deviation 1.825 0.798 0.644 0.593 0.515
Proportion of Variance 0.666 0.127 0.083 0.070 0.053
Cumulative Proportion 0.666 0.794 0.877 0.947 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted Feature Cluster IgG PC1: p=.28
Maternal Tdap+ vs. Tdap- boosted Feature Cluster IgG PC2: p=.075

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
Maternal Tdap+ vs. Tdap- boosted TT UMAP1: p=.71
Maternal Tdap+ vs. Tdap- boosted TT UMAP2: p=.38

Response Cluster: 1

Features: DT_ADCD, DT_FcgR2a, 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 PC7
Standard deviation 2.002 1.084 0.812 0.666 0.601 0.518 0.290
Proportion of Variance 0.573 0.168 0.094 0.063 0.052 0.038 0.012
Cumulative Proportion 0.573 0.741 0.835 0.898 0.950 0.988 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted RCluster_ 1 PC1: p=.29
Maternal Tdap+ vs. Tdap- boosted RCluster_ 1 PC2: p=.74

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
Maternal Tdap+ vs. Tdap- boosted TT UMAP1: p=.31
Maternal Tdap+ vs. Tdap- boosted TT UMAP2: p=.12

Response Cluster: 2

Features: DT_ADCP, DT_ADNP, PRN_ADNP, PT_IgG2, PT_IgG4, TT_ADNP, TT_IgG4

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7
Standard deviation 1.483 1.162 0.979 0.899 0.837 0.778 0.615
Proportion of Variance 0.314 0.193 0.137 0.115 0.100 0.087 0.054
Cumulative Proportion 0.314 0.507 0.644 0.759 0.859 0.946 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted RCluster_ 2 PC1: p=.31
Maternal Tdap+ vs. Tdap- boosted RCluster_ 2 PC2: p=.12

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
Maternal Tdap+ vs. Tdap- boosted TT UMAP1: p=.27
Maternal Tdap+ vs. Tdap- boosted TT UMAP2: p=.64

Response Cluster: 3

Features: FHA_ADCP, FHA_ADNP, FHA_FcgR2a, FHA_FcgR3b, FHA_IgG, FHA_IgG1, TT_ADCP

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7
Standard deviation 2.040 1.003 0.796 0.729 0.594 0.521 0.214
Proportion of Variance 0.594 0.144 0.090 0.076 0.050 0.039 0.007
Cumulative Proportion 0.594 0.738 0.828 0.904 0.955 0.993 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted RCluster_ 3 PC1: p=.052
Maternal Tdap+ vs. Tdap- boosted RCluster_ 3 PC2: p=.18

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
Maternal Tdap+ vs. Tdap- boosted TT UMAP1: p=.055
Maternal Tdap+ vs. Tdap- boosted TT UMAP2: p=.0066

Response Cluster: 4

Features: DT_FcgR3b, PRN_ADCP, PRN_FcgR2a, PRN_FcgR3b, PRN_IgG, PRN_IgG1, TT_FcgR3b

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7
Standard deviation 2.036 1.068 0.797 0.704 0.590 0.451 0.175
Proportion of Variance 0.592 0.163 0.091 0.071 0.050 0.029 0.004
Cumulative Proportion 0.592 0.755 0.846 0.917 0.966 0.996 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted RCluster_ 4 PC1: p=.36
Maternal Tdap+ vs. Tdap- boosted RCluster_ 4 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
Maternal Tdap+ vs. Tdap- boosted TT UMAP1: p=.54
Maternal Tdap+ vs. Tdap- boosted TT UMAP2: p=.54

Response Cluster: 5

Features: PT_ADCP, PT_ADNP, PT_FcgR2a, PT_FcgR3b, PT_IgG, PT_IgG1

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6
Standard deviation 1.920 0.931 0.714 0.705 0.543 0.378
Proportion of Variance 0.615 0.144 0.085 0.083 0.049 0.024
Cumulative Proportion 0.615 0.759 0.844 0.927 0.976 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted RCluster_ 5 PC1: p=.085
Maternal Tdap+ vs. Tdap- boosted RCluster_ 5 PC2: p=.39

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
Maternal Tdap+ vs. Tdap- boosted TT UMAP1: p=.0043
Maternal Tdap+ vs. Tdap- boosted TT UMAP2: p=.0092

Response Cluster: 6

Features: DT_IgG, DT_IgG1, DT_IgG2, DT_IgG4, PRN_IgG2, PRN_IgG3, PRN_IgG4

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7
Standard deviation 1.690 1.166 0.943 0.821 0.767 0.620 0.499
Proportion of Variance 0.408 0.194 0.127 0.096 0.084 0.055 0.036
Cumulative Proportion 0.408 0.602 0.729 0.825 0.910 0.964 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted RCluster_ 6 PC1: p=.51
Maternal Tdap+ vs. Tdap- boosted RCluster_ 6 PC2: p=.16

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
Maternal Tdap+ vs. Tdap- boosted TT UMAP1: p=.59
Maternal Tdap+ vs. Tdap- boosted TT UMAP2: p=.57

Response Cluster: 7

Features: DT_IgG3, FHA_IgG2, FHA_IgG3, FHA_IgG4, PT_IgG3, TT_IgG, TT_IgG1, TT_IgG2, TT_IgG3

Proportion of Variance

summary for first 5 principal components (PC)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9
Standard deviation 1.805 1.170 1.123 0.897 0.837 0.765 0.674 0.558 0.508
Proportion of Variance 0.362 0.152 0.140 0.089 0.078 0.065 0.050 0.035 0.029
Cumulative Proportion 0.362 0.514 0.654 0.743 0.821 0.886 0.937 0.971 1.000

Plot of PC1 vs PC2 scores

Comparison of principle components by arm
Maternal Tdap+ vs. Tdap- boosted RCluster_ 7 PC1: p=.32
Maternal Tdap+ vs. Tdap- boosted RCluster_ 7 PC2: p=.2

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
Maternal Tdap+ vs. Tdap- boosted TT UMAP1: p=.36
Maternal Tdap+ vs. Tdap- boosted TT UMAP2: p=.59


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