title: Journaled string tree-a scalable data structure for analyzing thousands of similar genomes on your laptop.
abstract: BACKGROUND
  Next-generation sequencing (NGS) has revolutionized biomedical research in the past decade and led to a continuous stream of developments in bioinformatics, addressing the need for fast and space-efficient solutions for analyzing NGS data. Often researchers need to analyze a set of genomic sequences that stem from closely related species or are indeed individuals of the same species. Hence, the analyzed sequences are similar. For analyses where local changes in the examined sequence induce only local changes in the results, it is obviously desirable to examine identical or similar regions not repeatedly.
  
  
  RESULTS
  In this work, we provide a datatype that exploits data parallelism inherent in a set of similar sequences by analyzing shared regions only once. In real-world experiments, we show that algorithms that otherwise would scan each reference sequentially can be speeded up by a factor of 115.
authors.affiliation: Department of Mathematics and Computer Science, Freie Universität Berlin, Takustr. 9, 14195 Berlin, Germany.
authors.forename: René
authors.initials: R
authors.lastname: Rahn
authors.affiliation: Department of Mathematics and Computer Science, Freie Universität Berlin, Takustr. 9, 14195 Berlin, Germany.
authors.forename: David
authors.initials: D
authors.lastname: Weese
authors.affiliation: Department of Mathematics and Computer Science, Freie Universität Berlin, Takustr. 9, 14195 Berlin, Germany.
authors.forename: Knut
authors.initials: K
authors.lastname: Reinert
mesh_terms: D000465:Algorithms; D003201:Computers; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*