Fig. 2
From: IDTAXA: a novel approach for accurate taxonomic classification of microbiome sequences
Variability in sequence similarity at the same confidence level. During leave-one-out cross-validation with the RDP training set, for each singleton sequence, we computed the distance to the nearest sequence in the group to which it was assigned. The IDTAXA algorithm only assigned a high confidence to sequences that had a low distance to the query sequence being classified. In contrast, all other k-mer approaches assigned high confidences even when all of the sequences in the group were distant to the query sequence. The curves indicate the cubic spline that best fits the data