Composite repetition-aware data structures

Djamal Belazzougui; Fabio Cunial; Travis Gagie; Nicola Prezza; Mathieu Raffinot

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arXiv · 1502.05937

Composite repetition-aware data structures

Djamal Belazzougui·Fabio Cunial·Travis Gagie·Nicola Prezza·Mathieu Raffinot

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Abstract

In highly repetitive strings, like collections of genomes from the same species, distinct measures of repetition all grow sublinearly in the length of the text, and indexes targeted to such strings typically depend only on one of these measures. We describe two data structures whose size depends on multiple measures of repetition at once, and that provide competitive tradeoffs between the time for counting and reporting all the exact occurrences of a pattern, and the space taken by the structure. The key component of our constructions is the run-length encoded BWT (RLBWT), which takes space proportional to the number of BWT runs: rather than augmenting RLBWT with suffix array samples, we combine it with data structures from LZ77 indexes, which take space proportional to the number of LZ77 factors, and with the compact directed acyclic word graph (CDAWG), which takes space proportional to the number of extensions of maximal repeats. The combination of CDAWG and RLBWT enables also a new representation of the suffix tree, whose size depends again on the number of extensions of maximal repeats, and that is powerful enough to support matching statistics and constant-space traversal.

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BibTeX RIS

Djamal Belazzougui, Fabio Cunial, Travis Gagie, Nicola Prezza, Mathieu Raffinot. 2015-02-20. Composite repetition-aware data structures. https://arxiv.org/abs/1502.05937

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