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@ARTICLE{Kim2015-mu,
  title     = "{HISAT}: a fast spliced aligner with low memory requirements",
  author    = "Kim, Daehwan and Langmead, Ben and Salzberg, Steven L",
  abstract  = "HISAT (hierarchical indexing for spliced alignment of
               transcripts) is a highly efficient system for aligning reads
               from RNA sequencing experiments. HISAT uses an indexing scheme
               based on the Burrows-Wheeler transform and the Ferragina-Manzini
               (FM) index, employing two types of indexes for alignment: a
               whole-genome FM index to anchor each alignment and numerous
               local FM indexes for very rapid extensions of these alignments.
               HISAT's hierarchical index for the human genome contains 48,000
               local FM indexes, each representing a genomic region of ∼64,000
               bp. Tests on real and simulated data sets showed that HISAT is
               the fastest system currently available, with equal or better
               accuracy than any other method. Despite its large number of
               indexes, HISAT requires only 4.3 gigabytes of memory. HISAT
               supports genomes of any size, including those larger than 4
               billion bases.",
  journal   = "Nat. Methods",
  volume    =  12,
  pages     = "357",
  year      =  2015
}
