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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