Figure 3.

Aberration calling accuracy. The ROC-curves show the sensitivity and specificity for a sequence of thresholds as calculated by comparing aberration calls to the classifications made in a MLPA-analysis on the same data material. In panel (a), classifications were made based on PCF segmentations found for a wide range of γ-values. Notably, the classification accuracy is not affected much by the choice of γ, except to some extent for very low values. Panel (b) shows that aberration calls based on multi-sample PCF segmentations are about as accurate as those based on single sample PCF. In panel (c), ROC-curves are shown for calls made on the basis of the segmentations found by PCF and CBS, a running median with window size 50 and raw data. In terms of aberration calling accuracy, PCF and CBS give nearly the same results, while using the running median gives slightly less accurate classifications. Using only raw data leads to much poorer accuracy. Note the range on the ordinate axis.

Nilsen et al. BMC Genomics 2012 13:591   doi:10.1186/1471-2164-13-591
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