A De Novo Genome Assembly Algorithm for Repeats and Nonrepeats

Background. Next generation sequencing platforms can generate shorter reads, deeper coverage, and higher throughput than those of the Sanger sequencing. These short reads may be assembled de novo before some specific genome analyses. Up to now, the performances of assembling repeats of these current assemblers are very poor. Results. To improve this problem, we proposed a new genome assembly algorithm, named SWA, which has four properties: (1) assembling repeats and nonrepeats; (2) adopting a new overlapping extension strategy to extend each seed; (3) adopting sliding window to filter out the sequencing bias; and (4) proposing a compensational mechanism for low coverage datasets. SWA was evaluated and validated in both simulations and real sequencing datasets. The accuracy of assembling repeats and estimating the copy numbers is up to 99% and 100%, respectively. Finally, the extensive comparisons with other eight leading assemblers show that SWA outperformed others in terms of completeness and correctness of assembling repeats and nonrepeats. Conclusions. This paper proposed a new de novo genome assembly method for resolving complex repeats. SWA not only can detect where repeats or nonrepeats are but also can assemble them completely from NGS data, especially for assembling repeats. This is the advantage over other assemblers.