Figure 5
Assessment of transferability of classifiers across platform using T-index scores. A total of 54 permutations were tested to assess cross-platform predictivity of classifiers, which consisted of two platforms, three ACs, three approaches for generating CT sets and three classification algorithms (that is, support vector machine (SVM), KNN and DF). AFX → AGL (or AGL → AFX) denotes that the classifiers were generated from the Affymetrix (or Agilent) platform and then used to predict the test sets that profiled by the opposite platform. A T-index score was calculated for each permutation to evaluate the cross-platform predictivity based on a comparative analysis of prediction results obtained from both of the test sets that each set of classifiers was used to predict. (a) Compares the T-index scores that were generated by the three ACs, while (b) compares the results that were achieved with the three classification algorithms. (c) Depicts the T-index scores that were obtained with the three approaches for generating CT lists across the two platforms. The results indicate that the cross-platform predictivity was independent of the AC and the method for identifying the CTs, but varied slightly with the classification algorithms.
