The Receiver Operating Characteristic (ROC) curves for simulations. (a)-(c) We plot the number of true allele-specific SNPs (i.e., true positives, TP) among the top q ranked SNPs in each dataset against the rank cutoff q. Results for different methods in three representative datasets in simulation 1 are shown. Results in all other datasets were similar. (d) For each ranking method and each dataset, we computed the area under the ROC curve (AUC) using the 2000 top ranked SNPs. dAUC, the proportion of improvement of AUC brought by iASeq over the best AUC obtained from the single-dataset based methods, was computed for each dataset. dAUC>0 means iASeq brings improvement. The distribution of dAUC in all 40 datasets is shown for simulation 1. (e)-(g) Results in three representative datasets from simulation 2. Results in all other datasets were similar. (h) The distribution of dAUC in all 40 datasets is shown for simulation 2.
Wei et al. BMC Genomics 2012 13:681 doi:10.1186/1471-2164-13-681