EPR-dictionaries: A practical and fast data structure for constant time searches in unidirectional and bidirectional FM-indices

August 08, 2016 · Declared Dead · 🏛 Annual International Conference on Research in Computational Molecular Biology

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Authors Christopher Pockrandt, Marcel Ehrhardt, Knut Reinert arXiv ID 1608.02413 Category cs.DS: Data Structures & Algorithms Citations 13 Venue Annual International Conference on Research in Computational Molecular Biology Last Checked 3 months ago
Abstract
We introduce a new, practical method for conducting an exact search in a uni- and bidirectional FM index in $O(1)$ time per step while using $O(\log σ* n) + o(\log σ* σ* n)$ bits of space. This is done by replacing the binary wavelet tree by a new data structure, the Enhanced Prefixsum Rank dictionary (EPR-dictionary). We implemented this method in the SeqAn C++ library and experimentally validated our theoretical results. In addition we compared our implementation with other freely available implementations of bidirectional indices and show that we are between $\approx 2.6-4.8$ times faster. This will have a large impact for many bioinformatics applications that rely on practical implementations of (2)FM indices e.g. for read mapping. To our knowledge this is the first implementation of a constant time method for a search step in 2FM indices.
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