Relative Suffix Trees
Abstract
Suffix trees are one of the most versatile data structures in stringology, with many applications in bioinformatics. Their main drawback is their size, which can be tens of times larger than the input sequence. Much effort has been put into reducing the space usage, leading ultimately to compressed suffix trees. These compressed data structures can efficiently simulate the suffix tree, while using space proportional to a compressed representation of the sequence. In this work, we take a new approach to compressed suffix trees for repetitive sequence collections, such as collections of individual genomes. We compress the suffix trees of individual sequences relative to the suffix tree of a reference sequence. These relative data structures provide competitive time/space trade-offs, being almost as small as the smallest compressed suffix trees for repetitive collections, and competitive in time with the largest and fastest compressed suffix trees.
Cite
@article{arxiv.1508.02550,
title = {Relative Suffix Trees},
author = {Andrea Farruggia and Travis Gagie and Gonzalo Navarro and Simon J. Puglisi and Jouni Sirén},
journal= {arXiv preprint arXiv:1508.02550},
year = {2017}
}
Comments
Accepted to The Computer Journal. The implementation is available at https://github.com/jltsiren/relative-fm