title: Long read alignment based on maximal exact match seeds.
abstract: BACKGROUND
  The explosive growth of next-generation sequencing datasets poses a challenge to the mapping of reads to reference genomes in terms of alignment quality and execution speed. With the continuing progress of high-throughput sequencing technologies, read length is constantly increasing and many existing aligners are becoming inefficient as generated reads grow larger.
  
  
  RESULTS
  We present CUSHAW2, a parallelized, accurate, and memory-efficient long read aligner. Our aligner is based on the seed-and-extend approach and uses maximal exact matches as seeds to find gapped alignments. We have evaluated and compared CUSHAW2 to the three other long read aligners BWA-SW, Bowtie2 and GASSST, by aligning simulated and real datasets to the human genome. The performance evaluation shows that CUSHAW2 is consistently among the highest-ranked aligners in terms of alignment quality for both single-end and paired-end alignment, while demonstrating highly competitive speed. Furthermore, our aligner shows good parallel scalability with respect to the number of CPU threads.
  
  
  BACKGROUND
  CUSHAW2, written in C++, and all simulated datasets are available at http://cushaw2.sourceforge.net
  
  
  BACKGROUND
  liuy@uni-mainz.de; bertil.schmidt@uni-mainz.de
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Institut für Informatik, Johannes Gutenberg Universität Mainz, Mainz 55099, Germany. liuy@uni-mainz.de
authors.forename: Yongchao
authors.initials: Y
authors.lastname: Liu
authors.forename: Bertil
authors.initials: B
authors.lastname: Schmidt
mesh_terms: D000465:Algorithms; D002874:Chromosome Mapping; D015894:Genome, Human; D023281:Genomics / Q000379:methods; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software