Paper detail

BAUM: A DNA Assembler by Adaptive Unique Mapping and Local Overlap-Layout-Consensus

Genome assembly from the high-throughput sequencing (HTS) reads is a fundamental yet challenging computational problem. An intrinsic challenge is the uncertainty caused by the widespread repetitive elements. Here we get around the uncertainty using the notion of uniquely mapped (UM) reads, which motivated the design of a new assembler BAUM. It mainly consists of two types of iterations. The first type of iterations constructs initial contigs from a reference, say a genome of a species that could be quite distant, by adaptive read mapping, filtration by the reference's unique regions, and reference updating. A statistical test is proposed to split the layouts at possible structural variation sites. The second type of iterations includes mapping, scaffolding/contig-extension, and contig merging. We extend each contig by locally assembling the reads whose mates are uniquely mapped to an end of the contig. Instead of the de Bruijn graph method, we take the overlap-layout-consensus (OLC) paradigm. The OLC is implemented by parallel computation, and has linear complexity with respect to the number of contigs. The adjacent extended contigs are merged if their alignment is confirmed by the adjusted gap distance. Throughout the assembling, the mapping criterion is selected by probabilistic calculations. These innovations can be used complementary to the existing de novo assemblers. Applying this novel method to the assembly of wild rice Oryza longistaminata genome, we achieved much improved contig N50, 18.8k, compared with other assemblers. The assembly was further validated by contigs constructed from an independent library of long 454 reads.