Figure 4

Accuracy by minor allele frequency. Accuracy for the 610 k Quad training data after 0% (A), 1% (B) and 2% (C) of calls with lowest confidence were removed from the analysis. The x-axis in each plot shows MAF calculated from 0.05 (5%) to 0.5 (50%) in increments of 0.05 (5%). Similar plots are shown for the 610 k Quad test data, with figures D, E and F displaying accuracy after 0%, 1% and 2% of the calls with lowest confidence were dropped from the analysis. Ignoring the overall differences in accuracy, which are consistent with the results seen in Figure 1, we see that different methods vary in performance by MAF. For example, the accuracy profile of GenCall and Illuminus increases fairly monotonically as the frequency of the rarer allele increases, with lowest accuracy obtained for SNPs with a MAF of 5% or lower. GenoSNP and CRLMM are most accurate at calling rarer alleles, and have a more consistent accuracy profile as MAF varies. These trends are consistent as more SNPs are excluded from the analysis. As we have seen in other analyses, the more samples available, the better the performance of Illuminus with higher accuracy achieved on the training data (225 samples) compared to the test data (27 samples). In figures D, E and F, the accuracies at minor allele frequencies of 5% and 10% are not plotted for Illuminus as they fall are below 0.994 (0.928 and 0.987 respectively at 0% drop rate, 0.961 and 0.992 at 1% and 0.966 and 0.993 at 2%). For Illuminus and GenoSNP, SNPs assigned to the 'no call' class are excluded from the accuracy calculations. These figures show results for autosomal SNPs only.