Lightweight BWT construction for very large string collections

  • Bauer M
  • Cox A
  • Rosone G
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A modern DNA sequencing machine can generate a billion or more sequence fragments in a matter of days. The many uses of theBWT in compression and indexing are well known, but the computational de- mands of creating the BWT of datasets this large have prevented its applications from being widely explored in this context. We address this obstacle by presenting two algorithms capable of com- puting the BWT of very large string collections. The algorithms are lightweight in that the first needs O(mlogm)bits of memoryto process m strings and the memory requirements of the second are constant with respect to m. We evaluate our algorithms on collections of up to 1 billion strings and compare their performance to other approaches on smaller datasets. Although our tests were on collections of DNA sequences of uniform length, the algorithms themselves apply to any string collection over any alphabet.

Author-supplied keywords

  • BWT
  • next-generation sequencing
  • text indexes

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  • Markus J. Bauer

  • Anthony J. Cox

  • Giovanna Rosone

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