An illustration of overlap error rate estimation, repeat identification, and splitting. (A) A histogram of all best edge error rates with the auto-selected threshold shown as a dashed line for the Drosophila melanogaster PacBio data set. All overlaps up to 4% error were computed. However, the modal error rate is 0.25% (0.25% median, 0.15% MAD), and Canu chose to use only overlaps <1.6% error for graph construction on this data set. (B) The dashed line shows the global error rate threshold (1.6%), and the profile shows the locally computed error rate for the largest contig in this assembly. Only overlaps consistent with this local error rate are considered as potential alternate paths when supplementing the initial BOG. By adjusting the error rate for each contig, Canu can separate diverged repeats without making an assumption of uniform read error across the assembly. (C) The contig is shown as a black line with arrows on both sides, indicating Bogart extends a path in both the 5′ and 3′ directions until encountering no overlaps or a read that is already incorporated in another contig. Repeat regions annotated by conflicting reads are shown above the contig. The reads align to part of the contig (the repeat) but indicate a different boundary sequence. A single read (blue line) spans the full repeat region, indicating the contig reconstruction is correct. (D) Repeat regions annotated by conflicting reads as before. In this case, no single read spans the full repeat region, and the initial contig was built using the overlap between two blue reads. The contig is split if the overlap between the two blue reads is not significantly better than the overlap from either blue read to the conflicting red read.
