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Prefix-Free Parsing for Building Big BWTs

Authors Christina Boucher , Travis Gagie , Alan Kuhnle , Giovanni Manzini

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Author Details

Christina Boucher
  • CISE, University of Florida, Gainesville, FL, USA
Travis Gagie
  • EIT, Diego Portales University, Santiago, Chile, 1exCeBiB, Santiago, Chile
Alan Kuhnle
  • CISE, University of Florida, Gainesville, FL, USA
Giovanni Manzini
  • University of Eastern Piedmont, Alessandria, Italy, 1exIIT, CNR, Pisa, Italy

Funding

  • Boucher, Christina: Partially supported by National Science Foundation grant 1618814.
  • Gagie, Travis: Partially supported by FONDECYT grant 1171058.
  • Kuhnle, Alan: Partially supported by National Science Foundation grant 1618814 and a post-doctoral fellowship from the University of Florida Informatics Institute.
  • Manzini, Giovanni: Partially supported by PRIN grant 201534HNXC

Cite As Get BibTex

Christina Boucher, Travis Gagie, Alan Kuhnle, and Giovanni Manzini. Prefix-Free Parsing for Building Big BWTs. In 18th International Workshop on Algorithms in Bioinformatics (WABI 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 113, pp. 2:1-2:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018) https://doi.org/10.4230/LIPIcs.WABI.2018.2

Abstract

High-throughput sequencing technologies have led to explosive growth of genomic databases; one of which will soon reach hundreds of terabytes. For many applications we want to build and store indexes of these databases but constructing such indexes is a challenge. Fortunately, many of these genomic databases are highly-repetitive - a characteristic that can be exploited and enable the computation of the Burrows-Wheeler Transform (BWT), which underlies many popular indexes. In this paper, we introduce a preprocessing algorithm, referred to as prefix-free parsing, that takes a text T as input, and in one-pass generates a dictionary D and a parse P of T with the property that the BWT of T can be constructed from D and P using workspace proportional to their total size and O(|T|)-time. Our experiments show that D and P are significantly smaller than T in practice, and thus, can fit in a reasonable internal memory even when T is very large. Therefore, prefix-free parsing eases BWT construction, which is pertinent to many bioinformatics applications.

Subject Classification

ACM Subject Classification
  • Theory of computation → Design and analysis of algorithms
Keywords
  • Burrows-Wheeler Transform
  • prefix-free parsing
  • compression-aware algorithms
  • genomic databases

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Supplementary Materials

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