Practical compressed suffix trees

Abstract

The suffix tree is an extremely important data structure in bioinformatics. Classical implementations require much space, which renders them useless to handle large sequence collections. Recent research has obtained various compressed representations for suffix trees, with widely different space-time tradeoffs. In this paper we show how the use of range min-max trees yields novel representations achieving practical space/time tradeoffs. In addition, we show how those trees can be modified to index highly repetitivecollections, obtaining the first compressed suffix tree representation thateffectively adapts to that scenario. © 2013 by the authors; licensee MDPI, Basel, Switzerland.