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Table 1 Diversity (α D) and Evenness (α E) profiles classify TCR (dataset 1) and BCR (dataset 2) immune repertoires by immunological status with high accuracy

From: A bioinformatic framework for immune repertoire diversity profiling enables detection of immunological status

  BACC (%) Sensitivity (%) Specificity (%) Significance (p-value) Median number of alpha-values used
Dataset 1      
CD4-Diversity \( \left(\overrightarrow{{}^{\alpha }D}\right) \): Month 2 versus Baseline + Month 12 86.5 72.9 100 0 8
CD4-Evenness \( \left(\overrightarrow{{}^{\alpha }E}\right) \): Month 2 versus Baseline + Month 12 91.7 83.3 100 0 11
CD8-Diversity \( \left(\overrightarrow{{}^{\alpha }D}\right) \): Month 2 versus Baseline + Month 12 79.2 58.3 100 0 9
CD8-Evenness \( \left(\overrightarrow{{}^{\alpha }E}\right) \): Month 2 versus Baseline + Month 12 96.9 93.8 100 0 6
Dataset 2
Diversity: Healthy versus CLL \( \left(\overrightarrow{{}^{\alpha }D}\right) \) 88 77 100 0 5
Evenness: Healthy versus CLL \( \left(\overrightarrow{{}^{\alpha }E}\right) \) 84 77 91 0 2
  1. The median number of alpha-values employed to reach optimal prediction accuracy (BACC) ranged between 2 and 11. BACCs were computed using nested leave-one-out cross-validation and were regarded as significant if p < 0.01. BACC ((Sensitivity + Specificity)/2), balanced prediction accuracy. Diversity and Evenness profiles were calculated in a range of alpha = 0 to alpha = 10 with a step size of 0.2