Fig. 3

Performance evaluation of FusorSV. The results of 1000 rounds of cross-validation where 18 samples were used to train a fusion model and the remaining nine samples were tested. Being closer to the upper right corner means better performance, with the solid dot depicting the average for all samples. FusorSV improves performance by utilizing multiple algorithms while making more total calls than integrative consensus methods like MetaSV