Figure 6

Comparison of CCA with other classification methods using the Gata3 dataset. The classification ability of CCA was compared with other classification methods. The Th dataset was used as a training data (explanatory variables for CCA), and WT data from the Stat3 dataset was used as a test data. (a) Sensitivity and accuracy of those methods are plotted, using various numbers of genes (n; between 10 and 200). The numbers of condition positive (Th17 differentiated cells) and condition negative (all other samples) are four and twelve, respectively, in all the analyses. (b) Test dataset was resampled using a jackknife approach, and the classification methods were compared for sensitivity and accuracy. The number of genes used was either 20 (upper panels) or 200 (lower panels). Error bar indicates 95% confidence interval.