Genome reassembly with high-throughput sequencing data.
BACKGROUND
Recent studies in genomics have highlighted the significance of structural variation in determining individual variation. Current methods for identifying structural variation, however, are predominantly focused on either assembling whole genomes from scratch, or identifying the relatively small changes between a genome and a reference sequence. While significant progress has been made in recent years on both de novo assembly and resequencing (read mapping) methods, few attempts have been made to bridge the gap between them.


RESULTS
In this paper, we present a computational method for incorporating a reference sequence into an assembly algorithm. We propose a novel graph construction that builds upon the well-known de Bruijn graph to incorporate the reference, and describe a simple algorithm, based on iterative message passing, which uses this information to significantly improve assembly results. We validate our method by applying it to a series of 5 Mb simulation genomes derived from both mammalian and bacterial references. The results of applying our method to this simulation data are presented along with a discussion of the benefits and drawbacks of this technique.
Department of Computer Science, University of California Los Angeles, Los Angeles, California, USA.
Nathaniel
N
Parrish
Benjamin
B
Sudakov
Eleazar
E
Eskin
D000465:Algorithms; D000818:Animals; D019295:Computational Biology; D016678:Genome; D059014:High-Throughput Nucleotide Sequencing; D051379:Mice