Candidate blood transcriptional markers discriminate sepsis due to B. pseudomallei from sepsis due to other organisms. (a) Patients with sepsis in R5 of the training set (comprising eight patients with melioidosis (pink rectangles) and six patients with sepsis caused by other organisms (green rectangles)) were subjected to class prediction analysis (K-nearest neighbors (kNN)) using the leave-one-out cross-validation scheme. This algorithm identified 37 classifiers that discriminated samples with 100% accuracy in the training set. (b) Independent validation of the 37 predictors was performed with the equivalent region R9 in test set 1, including 11 patients with melioidosis (pink) and 7 patients with sepsis caused by other organisms (green). The predictors correctly classified 14 of the 18 samples (78% accuracy).
Pankla et al. Genome Biology 2009 10:R127 doi:10.1186/gb-2009-10-11-r127