title: HGA: de novo genome assembly method for bacterial genomes using high coverage short sequencing reads.
abstract: BACKGROUND
  Current high-throughput sequencing technologies generate large numbers of relatively short and error-prone reads, making the de novo assembly problem challenging. Although high quality assemblies can be obtained by assembling multiple paired-end libraries with both short and long insert sizes, the latter are costly to generate. Recently, GAGE-B study showed that a remarkably good assembly quality can be obtained for bacterial genomes by state-of-the-art assemblers run on a single short-insert library with very high coverage.
  
  
  RESULTS
  In this paper, we introduce a novel hierarchical genome assembly (HGA) methodology that takes further advantage of such very high coverage by independently assembling disjoint subsets of reads, combining assemblies of the subsets, and finally re-assembling the combined contigs along with the original reads.
  
  
  CONCLUSIONS
  We empirically evaluated this methodology for 8 leading assemblers using 7 GAGE-B bacterial datasets consisting of 100 bp Illumina HiSeq and 250 bp Illumina MiSeq reads, with coverage ranging from 100x- ∼200x. The results show that for all evaluated datasets and using most evaluated assemblers (that were used to assemble the disjoint subsets), HGA leads to a significant improvement in the quality of the assembly based on N50 and corrected N50 metrics.
authors.affiliation: Computer Science & Engineering Department, University of Connecticut, Storrs, 06269, CT, USA. aaa10013@engr.uconn.edu.
authors.forename: Anas A
authors.initials: AA
authors.lastname: Al-Okaily
mesh_terms: D020451:Contig Mapping; D015723:Gene Library; D016680:Genome, Bacterial; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods; D012984:Software