HINGE: long-read assembly achieves optimal repeat resolution

Abstract

Long-read sequencing technologies have the potential to produce gold-standard de novo genome assemblies, but fully exploiting error-prone reads to resolve repeats remains a challenge. Aggressive approaches to repeat resolution often produce misassemblies, and conservative approaches lead to unnecessary fragmentation. We present HINGE, an assembler that seeks to achieve 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 bacterial data sets from the NCTC project. HINGE produces more finished assemblies than Miniasm and the manual pipeline of NCTC based on the HGAP assembler and Circlator. HINGE also allows us to identify 40 data sets 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 such as the NCTC pipeline and FALCON either fragment the assembly or resolve the ambiguity arbitrarily.

The genome of cowpea (Vigna unguiculata[L.] Walp.)

“…Eight draft assemblies were generated, six of which were produced with CANU v1.3 (Berlin et al, 2015;Koren et al, 2017), one with FALCON v0.7.3 (Chin et al, 2016) and one with ABRUIJN v0.4 . HINGE v0.41 (Kamath et al, 2017) was also tested on this dataset, but at that time the tool required the entire alignment file (over 2 Tb) to fit in primary memory and we did not have the computational resources to handle it. CANU v1.3 was run with different settings for the error correction stage on the entire dataset of~6 M reads (two CANU runs were optimized for highly repetitive genomes).…”

New advances in sequence assembly

“…However, the massive read lengths and increased error rate of these new technologies have also required updated assembly methods. This issue includes three new assembly tools designed specifically for long-read PacBio and Nanopore data: Canu , HINGE (Kamath et al 2017), and Racon (Vaser et al 2017).…”

CONSENT: Scalable long read self-correction and assembly polishing with multiple sequence alignment

“…In contrast to second-generation technologies, producing reads reaching lengths of a few hundreds base pairs, they allow the sequencing of much longer reads (10 kbp on average (Sedlazeck et al, 2018b), and up to >1 million bps (Jain et al, 2018)). These long reads are expected to solve various problems, such as contig and haplotype assembly (Patterson et al, 2015;Kamath et al, 2017), scaffolding (Cao et al, 2017), and structural variant calling (Sedlazeck et al, 2018a). However, they are very noisy.…”