TY - JOUR T1 - HINGE: Long-Read Assembly Achieves Optimal Repeat Resolution JF - bioRxiv DO - 10.1101/062117 SP - 062117 AU - Govinda M. Kamath AU - Ilan Shomorony AU - Fei Xia AU - Thomas A. Courtade AU - David N. Tse Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/07/05/062117.abstract N2 - Long-read sequencing technologies have potential to produce gold-standard de novo genome assemblies, but fully exploiting error-prone reads to resolve repeats remains a challenge1. Aggressive approaches to repeat resolution often produce mis-assemblies, and conservative approaches lead to unnecessary fragmentation. We present HINGE, an assembler that achieves optimal repeat resolution by distinguishing repeats that can be resolved given the data from those that cannot. This is accomplished by adding "hinges" to reads for constructing an overlap graph where only unresolvable repeats are merged. As a result, HINGE combines the error resilience of overlap-based assemblers with repeat-resolution capabilities of de Bruijn graph assemblers. HINGE was evaluated on the long-read datasets from the NCTC project2. Besides producing more finished assemblies than the manual pipeline of NCTC based on the HGAP assembler3 and Circlator4, HINGE allows us to identify 40 datasets where unresolvable repeats prevent the reliable construction of a unique finished assembly. In these cases, HINGE outputs a visually interpretable assembly graph that encodes all possible finished assemblies consistent with the reads, while other approaches either fragment the assembly or resolve the ambiguity arbitrarily. ER -