Document

**Published in:** LIPIcs, Volume 301, 22nd International Symposium on Experimental Algorithms (SEA 2024)

For taxonomic classification, we are asked to index the genomes in a phylogenetic tree such that later, given a DNA read, we can quickly choose a small subtree likely to contain the genome from which that read was drawn. Although popular classifiers such as Kraken use k-mers, recent research indicates that using maximal exact matches (MEMs) can lead to better classifications. For example, we can
- build an augmented FM-index over the the genomes in the tree concatenated in left-to-right order;
- for each MEM in a read, find the interval in the suffix array containing the starting positions of that MEM’s occurrences in those genomes;
- find the minimum and maximum values stored in that interval;
- take the lowest common ancestor (LCA) of the genomes containing the characters at those positions. This solution is practical, however, only when the total size of the genomes in the tree is fairly small. In this paper we consider applying the same solution to three lossily compressed representations of the genomes' concatenation:
- a KATKA kernel, which discards characters that are not in the first or last occurrence of any k_max-tuple, for a parameter k_max;
- a minimizer digest;
- a KATKA kernel of a minimizer digest. With a test dataset and these three representations of it, simulated reads and various parameter settings, we checked how many reads' longest MEMs occurred only in the sequences from which those reads were generated ("true positive" reads). For some parameter settings we achieved significant compression while only slightly decreasing the true-positive rate.

Dominika Draesslerová, Omar Ahmed, Travis Gagie, Jan Holub, Ben Langmead, Giovanni Manzini, and Gonzalo Navarro. Taxonomic Classification with Maximal Exact Matches in KATKA Kernels and Minimizer Digests. In 22nd International Symposium on Experimental Algorithms (SEA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 301, pp. 10:1-10:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{draesslerova_et_al:LIPIcs.SEA.2024.10, author = {Draesslerov\'{a}, Dominika and Ahmed, Omar and Gagie, Travis and Holub, Jan and Langmead, Ben and Manzini, Giovanni and Navarro, Gonzalo}, title = {{Taxonomic Classification with Maximal Exact Matches in KATKA Kernels and Minimizer Digests}}, booktitle = {22nd International Symposium on Experimental Algorithms (SEA 2024)}, pages = {10:1--10:13}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-325-6}, ISSN = {1868-8969}, year = {2024}, volume = {301}, editor = {Liberti, Leo}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2024.10}, URN = {urn:nbn:de:0030-drops-203756}, doi = {10.4230/LIPIcs.SEA.2024.10}, annote = {Keywords: Taxonomic classification, metagenomics, KATKA, maximal exact matches, string kernels, minimizer digests} }

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**Published in:** LIPIcs, Volume 296, 35th Annual Symposium on Combinatorial Pattern Matching (CPM 2024)

The LCP array is an important tool in stringology, allowing to speed up pattern matching algorithms and enabling compact representations of the suffix tree. Recently, Conte et al. [DCC 2023] and Cotumaccio et al. [SPIRE 2023] extended the definition of this array to Wheeler DFAs and, ultimately, to arbitrary labeled graphs, proving that it can be used to efficiently solve matching statistics queries on the graph’s paths. In this paper, we provide the first efficient algorithm building the LCP array of a directed labeled graph with n nodes and m edges labeled over an alphabet of size σ. The first step is to transform the input graph G into a deterministic Wheeler pseudoforest G_{is} with O(n) edges encoding the lexicographically- smallest and largest strings entering in each node of the original graph. Using state-of-the-art algorithms, this step runs in O(min{mlog n, m+n²}) time on arbitrary labeled graphs, and in O(m) time on Wheeler DFAs. The LCP array of G stores the longest common prefixes between those strings, i.e. it can easily be derived from the LCP array of G_{is}. After arguing that the natural generalization of a compact-space LCP-construction algorithm by Beller et al. [J. Discrete Algorithms 2013] runs in time Ω(nσ) on pseudoforests, we present a new algorithm based on dynamic range stabbing building the LCP array of G_{is} in O(nlog σ) time and O(nlogσ) bits of working space. Combined with our reduction, we obtain the first efficient algorithm to build the LCP array of an arbitrary labeled graph. An implementation of our algorithm is publicly available at https://github.com/regindex/Labeled-Graph-LCP.

Jarno N. Alanko, Davide Cenzato, Nicola Cotumaccio, Sung-Hwan Kim, Giovanni Manzini, and Nicola Prezza. Computing the LCP Array of a Labeled Graph. In 35th Annual Symposium on Combinatorial Pattern Matching (CPM 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 296, pp. 1:1-1:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{alanko_et_al:LIPIcs.CPM.2024.1, author = {Alanko, Jarno N. and Cenzato, Davide and Cotumaccio, Nicola and Kim, Sung-Hwan and Manzini, Giovanni and Prezza, Nicola}, title = {{Computing the LCP Array of a Labeled Graph}}, booktitle = {35th Annual Symposium on Combinatorial Pattern Matching (CPM 2024)}, pages = {1:1--1:15}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-326-3}, ISSN = {1868-8969}, year = {2024}, volume = {296}, editor = {Inenaga, Shunsuke and Puglisi, Simon J.}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2024.1}, URN = {urn:nbn:de:0030-drops-201113}, doi = {10.4230/LIPIcs.CPM.2024.1}, annote = {Keywords: LCP array, Wheeler automata, prefix sorting, pattern matching, sorting} }

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**Published in:** LIPIcs, Volume 296, 35th Annual Symposium on Combinatorial Pattern Matching (CPM 2024)

Deterministic Finite Wheeler Automata are a natural generalisation to regular languages of the theory of compressed data structures originated by the introduction of the Burrows-Wheeler transform. Indeed, if we can find a Wheeler automaton recognizing a given language L, such automaton can be used to design time and space efficient algorithms for representing and searching L.
In this paper we introduce an alternative representation of Deterministic Wheeler Automata by showing that a natural map between strings and rational numbers in ℚ [0,1) can be extended to represent the automaton’s states as intervals in ℚ [0,1). Using this representation it emerges a natural relationship between automata properties and some properties of real numbers. In addition, such representation enables us to formulate problems related to automata in a numerical setting. Although at the moment the numerical approach does not lead to time efficient algorithms, we believe this new perspective deserves further consideration.
As a further demonstration of the convenience of this new representation, we use it to provide a simple proof of an unexpected result on regular languages. More precisely, we compare the size of the smallest Wheeler automaton recognizing a given language L with respect to the size of the smallest automaton, possibly non-Wheeler, recognizing the same language. We show settings in which there can be an exponential gap between the two sizes, and we discuss the implications of this result on the problem of representing regular languages.

Giovanni Manzini, Alberto Policriti, Nicola Prezza, and Brian Riccardi. The Rational Construction of a Wheeler DFA. In 35th Annual Symposium on Combinatorial Pattern Matching (CPM 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 296, pp. 23:1-23:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{manzini_et_al:LIPIcs.CPM.2024.23, author = {Manzini, Giovanni and Policriti, Alberto and Prezza, Nicola and Riccardi, Brian}, title = {{The Rational Construction of a Wheeler DFA}}, booktitle = {35th Annual Symposium on Combinatorial Pattern Matching (CPM 2024)}, pages = {23:1--23:15}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-326-3}, ISSN = {1868-8969}, year = {2024}, volume = {296}, editor = {Inenaga, Shunsuke and Puglisi, Simon J.}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2024.23}, URN = {urn:nbn:de:0030-drops-201336}, doi = {10.4230/LIPIcs.CPM.2024.23}, annote = {Keywords: String Matching, Deterministic Finite Automata, Wheeler languages, Graph Indexing, Co-lexicographical Sorting} }

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**Published in:** LIPIcs, Volume 212, 32nd International Symposium on Algorithms and Computation (ISAAC 2021)

We revisit the fundamental problem of compressing an integer dictionary that supports efficient rank and select operations by exploiting two kinds of regularities arising in real data: repetitiveness and approximate linearity. Our first contribution is a Lempel-Ziv parsing properly enriched to also capture approximate linearity in the data and still be compressed to the kth order entropy. Our second contribution is a variant of the block tree structure whose space complexity takes advantage of both repetitiveness and approximate linearity, and results highly competitive in time too. Our third and final contribution is an implementation and experimentation of this last data structure, which achieves new space-time trade-offs compared to known data structures that exploit only one of the two regularities.

Paolo Ferragina, Giovanni Manzini, and Giorgio Vinciguerra. Repetition- and Linearity-Aware Rank/Select Dictionaries. In 32nd International Symposium on Algorithms and Computation (ISAAC 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 212, pp. 64:1-64:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{ferragina_et_al:LIPIcs.ISAAC.2021.64, author = {Ferragina, Paolo and Manzini, Giovanni and Vinciguerra, Giorgio}, title = {{Repetition- and Linearity-Aware Rank/Select Dictionaries}}, booktitle = {32nd International Symposium on Algorithms and Computation (ISAAC 2021)}, pages = {64:1--64:16}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-214-3}, ISSN = {1868-8969}, year = {2021}, volume = {212}, editor = {Ahn, Hee-Kap and Sadakane, Kunihiko}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ISAAC.2021.64}, URN = {urn:nbn:de:0030-drops-154974}, doi = {10.4230/LIPIcs.ISAAC.2021.64}, annote = {Keywords: Data compression, Compressed data structures, Entropy} }

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**Published in:** LIPIcs, Volume 201, 21st International Workshop on Algorithms in Bioinformatics (WABI 2021)

Compressed full-text indexes are one of the main success stories of bioinformatics data structures but even they struggle to handle some DNA readsets. This may seem surprising since, at least when dealing with short reads from the same individual, the readset will be highly repetitive and, thus, highly compressible. If we are not careful, however, this advantage can be more than offset by two disadvantages: first, since most base pairs are included in at least tens reads each, the uncompressed readset is likely to be at least an order of magnitude larger than the individual’s uncompressed genome; second, these indexes usually pay some space overhead for each string they store, and the total overhead can be substantial when dealing with millions of reads.
The most successful compressed full-text indexes for readsets so far are based on the Extended Burrows-Wheeler Transform (EBWT) and use a sorting heuristic to try to reduce the space overhead per read, but they still treat the reads as separate strings and thus may not take full advantage of the readset’s structure. For example, if we have already assembled an individual’s genome from the readset, then we can usually use it to compress the readset well: e.g., we store the gap-coded list of reads' starting positions; we store the list of their lengths, which is often highly compressible; and we store information about the sequencing errors, which are rare with short reads. There is nowhere, however, where we can plug an assembled genome into the EBWT.
In this paper we show how to use one or more assembled or partially assembled genome as the basis for a compressed full-text index of its readset. Specifically, we build a labelled tree by taking the assembled genome as a trunk and grafting onto it the reads that align to it, at the starting positions of their alignments. Next, we compute the eXtended Burrows-Wheeler Transform (XBWT) of the resulting labelled tree and build a compressed full-text index on that. Although this index can occasionally return false positives, it is usually much more compact than the alternatives. Following the established practice for datasets with many repetitions, we compare different full-text indices by looking at the number of runs in the transformed strings. For a human Chr19 readset our preliminary experiments show that eliminating separators characters from the EBWT reduces the number of runs by 19%, from 220 million to 178 million, and using the XBWT reduces it by a further 15%, to 150 million.

Travis Gagie, Garance Gourdel, and Giovanni Manzini. Compressing and Indexing Aligned Readsets. In 21st International Workshop on Algorithms in Bioinformatics (WABI 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 201, pp. 13:1-13:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{gagie_et_al:LIPIcs.WABI.2021.13, author = {Gagie, Travis and Gourdel, Garance and Manzini, Giovanni}, title = {{Compressing and Indexing Aligned Readsets}}, booktitle = {21st International Workshop on Algorithms in Bioinformatics (WABI 2021)}, pages = {13:1--13:21}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-200-6}, ISSN = {1868-8969}, year = {2021}, volume = {201}, editor = {Carbone, Alessandra and El-Kebir, Mohammed}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2021.13}, URN = {urn:nbn:de:0030-drops-143660}, doi = {10.4230/LIPIcs.WABI.2021.13}, annote = {Keywords: data compression, compact data structures, FM-index, Burrows-Wheeler Transform, EBWT, XBWT, DNA reads} }

Document

**Published in:** Dagstuhl Reports, Volume 9, Issue 6 (2020)

Dagstuhl Seminar 19241 ("25 Years of the Burrows-Wheeler Transform") took place from June 10th to 14th, 2019, and was attended by 45 people from 13 countries and the three fields of Algorithms and Data Structures, Bioinformatics, and Combinatorics on Words. There were four talks and a panel session for each field. Feedback was generally positive and we are confident the seminar fostered interdisciplinary connections and will eventually result in noteworthy joint publications.

Travis Gagie, Giovanni Manzini, Gonzalo Navarro, and Jens Stoye. 25 Years of the Burrows-Wheeler Transform (Dagstuhl Seminar 19241). In Dagstuhl Reports, Volume 9, Issue 6, pp. 55-68, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@Article{gagie_et_al:DagRep.9.6.55, author = {Gagie, Travis and Manzini, Giovanni and Navarro, Gonzalo and Stoye, Jens}, title = {{25 Years of the Burrows-Wheeler Transform (Dagstuhl Seminar 19241)}}, pages = {55--68}, journal = {Dagstuhl Reports}, ISSN = {2192-5283}, year = {2019}, volume = {9}, number = {6}, editor = {Gagie, Travis and Manzini, Giovanni and Navarro, Gonzalo and Stoye, Jens}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.9.6.55}, URN = {urn:nbn:de:0030-drops-114874}, doi = {10.4230/DagRep.9.6.55}, annote = {Keywords: Bioinformatics, Burrows-Wheeler Transform, Combinatorics on Words, Data Compression, Data Structures, Indexing, Sequence Alignment} }

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**Published in:** LIPIcs, Volume 128, 30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019)

The Burrows-Wheeler Transform is a string transformation that plays a fundamental role for the design of self-indexing compressed data structures. Over the years, researchers have successfully extended this transformation outside the domains of strings. However, efforts to find non-trivial alternatives of the original, now 25 years old, Burrows-Wheeler string transformation have met limited success. In this paper we bring new lymph to this area by introducing a whole new family of transformations that have all the "myriad virtues" of the BWT: they can be computed and inverted in linear time, they produce provably highly compressible strings, and they support linear time pattern search directly on the transformed string. This new family is a special case of a more general class of transformations based on context adaptive alphabet orderings, a concept introduced here. This more general class includes also the Alternating BWT, another invertible string transforms recently introduced in connection with a generalization of Lyndon words.

Raffaele Giancarlo, Giovanni Manzini, Giovanna Rosone, and Marinella Sciortino. A New Class of Searchable and Provably Highly Compressible String Transformations. In 30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 128, pp. 12:1-12:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{giancarlo_et_al:LIPIcs.CPM.2019.12, author = {Giancarlo, Raffaele and Manzini, Giovanni and Rosone, Giovanna and Sciortino, Marinella}, title = {{A New Class of Searchable and Provably Highly Compressible String Transformations}}, booktitle = {30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019)}, pages = {12:1--12:12}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-103-0}, ISSN = {1868-8969}, year = {2019}, volume = {128}, editor = {Pisanti, Nadia and P. Pissis, Solon}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2019.12}, URN = {urn:nbn:de:0030-drops-104833}, doi = {10.4230/LIPIcs.CPM.2019.12}, annote = {Keywords: Data Indexing and Compression, Burrows-Wheeler Transformation, Combinatorics on Words} }

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**Published in:** LIPIcs, Volume 113, 18th International Workshop on Algorithms in Bioinformatics (WABI 2018)

High-throughput sequencing technologies have led to explosive growth of genomic databases; one of which will soon reach hundreds of terabytes. For many applications we want to build and store indexes of these databases but constructing such indexes is a challenge. Fortunately, many of these genomic databases are highly-repetitive - a characteristic that can be exploited and enable the computation of the Burrows-Wheeler Transform (BWT), which underlies many popular indexes. In this paper, we introduce a preprocessing algorithm, referred to as prefix-free parsing, that takes a text T as input, and in one-pass generates a dictionary D and a parse P of T with the property that the BWT of T can be constructed from D and P using workspace proportional to their total size and O(|T|)-time. Our experiments show that D and P are significantly smaller than T in practice, and thus, can fit in a reasonable internal memory even when T is very large. Therefore, prefix-free parsing eases BWT construction, which is pertinent to many bioinformatics applications.

Christina Boucher, Travis Gagie, Alan Kuhnle, and Giovanni Manzini. Prefix-Free Parsing for Building Big BWTs. In 18th International Workshop on Algorithms in Bioinformatics (WABI 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 113, pp. 2:1-2:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{boucher_et_al:LIPIcs.WABI.2018.2, author = {Boucher, Christina and Gagie, Travis and Kuhnle, Alan and Manzini, Giovanni}, title = {{Prefix-Free Parsing for Building Big BWTs}}, booktitle = {18th International Workshop on Algorithms in Bioinformatics (WABI 2018)}, pages = {2:1--2:16}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-082-8}, ISSN = {1868-8969}, year = {2018}, volume = {113}, editor = {Parida, Laxmi and Ukkonen, Esko}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2018.2}, URN = {urn:nbn:de:0030-drops-93044}, doi = {10.4230/LIPIcs.WABI.2018.2}, annote = {Keywords: Burrows-Wheeler Transform, prefix-free parsing, compression-aware algorithms, genomic databases} }

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**Published in:** LIPIcs, Volume 113, 18th International Workshop on Algorithms in Bioinformatics (WABI 2018)

We propose an external memory algorithm for the computation of the BWT and LCP array for a collection of sequences. Our algorithm takes the amount of available memory as an input parameter, and tries to make the best use of it by splitting the input collection into subcollections sufficiently small that it can compute their BWT in RAM using an optimal linear time algorithm. Next, it merges the partial BWTs in external memory and in the process it also computes the LCP values. We show that our algorithm performs O(n maxlcp) sequential I/Os, where n is the total length of the collection and maxlcp is the maximum LCP value. The experimental results show that our algorithm outperforms the current best algorithm for collections of sequences with different lengths and when the average LCP of the collection is relatively small compared to the length of the sequences.
In the second part of the paper, we show that our algorithm can be modified to output two additional arrays that, combined with the BWT and LCP arrays, provide simple, scan based, external memory algorithms for three well known problems in bioinformatics: the computation of the all pairs suffix-prefix overlaps, the computation of maximal repeats, and the construction of succinct de Bruijn graphs.

Lavinia Egidi, Felipe A. Louza, Giovanni Manzini, and Guilherme P. Telles. External memory BWT and LCP computation for sequence collections with applications. In 18th International Workshop on Algorithms in Bioinformatics (WABI 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 113, pp. 10:1-10:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{egidi_et_al:LIPIcs.WABI.2018.10, author = {Egidi, Lavinia and Louza, Felipe A. and Manzini, Giovanni and Telles, Guilherme P.}, title = {{External memory BWT and LCP computation for sequence collections with applications}}, booktitle = {18th International Workshop on Algorithms in Bioinformatics (WABI 2018)}, pages = {10:1--10:14}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-082-8}, ISSN = {1868-8969}, year = {2018}, volume = {113}, editor = {Parida, Laxmi and Ukkonen, Esko}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2018.10}, URN = {urn:nbn:de:0030-drops-93122}, doi = {10.4230/LIPIcs.WABI.2018.10}, annote = {Keywords: Burrows-Wheeler Transform, Longest Common Prefix Array, All pairs suffix-prefix overlaps, Succinct de Bruijn graph, Maximal repeats} }

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**Published in:** LIPIcs, Volume 87, 25th Annual European Symposium on Algorithms (ESA 2017)

Encoding data structures store enough information to answer the queries they are meant to support but not enough to recover their underlying datasets. In this paper we give the first encoding data structure for the challenging problem of order-preserving pattern matching. This problem was introduced only a few years ago but has already attracted significant attention because of its applications in data analysis. Two strings are said to be an order-preserving match if the relative order of their characters is the same: e.g., (4, 1, 3, 2) and (10, 3, 7, 5) are an order-preserving match. We show how, given a string S[1..n] over an arbitrary alphabet of size sigma and a constant c >=1, we can build an O(n log log n)-bit encoding such that later, given a pattern P[1..m] with m >= log^c n, we can return the number of order-preserving occurrences of P in S in O(m) time. Within the same time bound we can also return the starting position of some order-preserving match for P in S (if such a match exists). We prove that our space bound is within a constant factor of optimal if log(sigma) = Omega(log log n); our query time is optimal if log(sigma) = Omega(log n). Our space bound contrasts with the Omega(n log n) bits needed in the worst case to store S itself, an index for order-preserving pattern matching with no restrictions on the pattern length, or an index for standard pattern matching even with restrictions on the pattern length. Moreover, we can build our encoding knowing only how each character compares to O(log^c n) neighbouring characters.

Travis Gagie, Giovanni Manzini, and Rossano Venturini. An Encoding for Order-Preserving Matching. In 25th Annual European Symposium on Algorithms (ESA 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 87, pp. 38:1-38:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{gagie_et_al:LIPIcs.ESA.2017.38, author = {Gagie, Travis and Manzini, Giovanni and Venturini, Rossano}, title = {{An Encoding for Order-Preserving Matching}}, booktitle = {25th Annual European Symposium on Algorithms (ESA 2017)}, pages = {38:1--38:15}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-049-1}, ISSN = {1868-8969}, year = {2017}, volume = {87}, editor = {Pruhs, Kirk and Sohler, Christian}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2017.38}, URN = {urn:nbn:de:0030-drops-78726}, doi = {10.4230/LIPIcs.ESA.2017.38}, annote = {Keywords: Compact data structures, encodings, order-preserving matching} }

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**Published in:** LIPIcs, Volume 78, 28th Annual Symposium on Combinatorial Pattern Matching (CPM 2017)

The famous Burrows-Wheeler Transform was originally defined for single strings but variations have been developed for sets of strings, labelled trees, de Bruijn graphs, alignments, etc. In this talk we propose a unifying view that includes many of these variations and that we hope will simplify the search for more.
Somewhat surprisingly we get our unifying view by considering the Nondeterministic Finite Automata related to different pattern-matching problems. We show that the state graphs associated with these automata have common properties that we summarize with the concept of a Wheeler graph. Using the notion of a Wheeler graph, we show that it is possible to process strings efficiently even if the automaton is nondeterministic. In addition, we show that Wheeler graphs can be compactly represented and traversed using up to three arrays with additional data structures supporting efficient rank and select operations. It turns out that these arrays coincide with, or are substantially equivalent to, the output of many Burrows-Wheeler Transform variants described in the literature.
This is joint work with Travis Gagie and Jouni Sirén.

Giovanni Manzini. Wheeler Graphs: Variations on a Theme by Burrows and Wheeler. In 28th Annual Symposium on Combinatorial Pattern Matching (CPM 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 78, p. 1:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{manzini:LIPIcs.CPM.2017.1, author = {Manzini, Giovanni}, title = {{Wheeler Graphs: Variations on a Theme by Burrows and Wheeler}}, booktitle = {28th Annual Symposium on Combinatorial Pattern Matching (CPM 2017)}, pages = {1:1--1:1}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-039-2}, ISSN = {1868-8969}, year = {2017}, volume = {78}, editor = {K\"{a}rkk\"{a}inen, Juha and Radoszewski, Jakub and Rytter, Wojciech}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2017.1}, URN = {urn:nbn:de:0030-drops-73343}, doi = {10.4230/LIPIcs.CPM.2017.1}, annote = {Keywords: compressed data structures, pattern matching} }

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