Average linear time and compressed space construction of the burrows-wheeler transform

Abstract

© Springer International Publishing Switzerland 2015. The Burrows-Wheeler Transform is a text permutation that has revolutionized the fields of pattern matching and text compression, bridging the gap existing between the two. In this paper we approach the BWT-construction problem generalizing a well-known algorithm—based on backward search and dynamic strings manipulation—to work in a context-wise fashion, using automata on words. Let n, σ, and Hk be the text length, the alphabet size, and the k-th order empirical entropy of the text, respectively. Moreover, let Hk = min{Hk +1, [log σ]}. Under the word RAM model with word size w ∈ Θ(log n), our algorithm builds theBWTin averageO(nHk) time using nHk+o(nHk) bits of space,where k = logσ(n/ log2 n) − 1. We experimentally show that our algorithm has very good performances (essentially linear time) on DNA sequences, using about 2.6 bits per input symbol in RAM.

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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