16 Search Results for "Myers, Gene"

Document
DOI: 10.4230/LIPIcs.STACS.2026.62
Relative Compressed Reverse Suffix Array

Authors: Muhammed Oguzhan Kulekci, Mano Prakash Parthasarathi, Rahul Shah, and Sharma V. Thankachan

Published in: LIPIcs, Volume 364, 43rd International Symposium on Theoretical Aspects of Computer Science (STACS 2026)

Abstract
Suffix trees and suffix arrays are two fundamental data structures in the field of string algorithms. For a string (a.k.a. text or sequence) of length n over an alphabet of size σ, these structures typically require O(nlog n) bits of space. The FM-index provides a compressed representation of the suffix array in ≈ nlog σ bits, allowing for efficient queries on both the suffix array and its inverse array in near logarithmic time. In certain applications, such as approximate pattern matching (i.e., with wildcards, mismatches, edits), there is a need to access the suffix array of a text, as well as the suffix array of text’s reverse. Motivated by this, we explore the possibility of encoding the suffix array of the reversed text in a compact form, assuming the availability of the FM-index for the original text. Our first solution is an O(n)-bit (relative) encoding of the suffix array of the reversed text, with the time for decoding an entry being only O(log^*n) times that of decoding an entry in the text’s suffix array using FM-index. We then demonstrate how to reduce the space to O(n/κ) bits for a parameter κ, while multiplicative factor in time becomes approximately O(κlog^*n+κ³). We can also support inverse suffix array and longest common extension queries on the reversed text. These results are achieved through some careful and non-trivial application of various succinct data structure techniques.
Cite as

Muhammed Oguzhan Kulekci, Mano Prakash Parthasarathi, Rahul Shah, and Sharma V. Thankachan. Relative Compressed Reverse Suffix Array. In 43rd International Symposium on Theoretical Aspects of Computer Science (STACS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 364, pp. 62:1-62:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{kulekci_et_al:LIPIcs.STACS.2026.62,
  author =	{Kulekci, Muhammed Oguzhan and Parthasarathi, Mano Prakash and Shah, Rahul and Thankachan, Sharma V.},
  title =	{{Relative Compressed Reverse Suffix Array}},
  booktitle =	{43rd International Symposium on Theoretical Aspects of Computer Science (STACS 2026)},
  pages =	{62:1--62:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-412-3},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{364},
  editor =	{Mahajan, Meena and Manea, Florin and McIver, Annabelle and Thắng, Nguy\~{ê}n Kim},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2026.62},
  URN =		{urn:nbn:de:0030-drops-255512},
  doi =		{10.4230/LIPIcs.STACS.2026.62},
  annote =	{Keywords: String Matching, Text Indexing, Data Structures, Suffix Trees}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.47
Fast and Lightweight Distributed Suffix Array Construction

Authors: Manuel Haag, Florian Kurpicz, Peter Sanders, and Matthias Schimek

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
The suffix array contains the lexicographical order of all suffixes of a text. It is one of the most well-studied text indices with applications in bioinformatics, compression, and pattern matching. The main bottleneck of distributed-memory suffix array construction algorithms is their memory requirements. Even careful implementations require 30×-60× the input size as working memory. We present a scalable and lightweight distributed-memory adaptation of the difference cover (DCX) suffix array construction algorithm. Our approach relies on novel bucketing and random chunk redistribution techniques which reduce our memory requirement to 20×-26× the input size for medium-sized inputs and to 14×-15× for large-sized inputs. Regarding running time, we achieve speedups of up to 5× over current state-of-the-art distributed suffix array construction algorithms.
Cite as

Manuel Haag, Florian Kurpicz, Peter Sanders, and Matthias Schimek. Fast and Lightweight Distributed Suffix Array Construction. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 47:1-47:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{haag_et_al:LIPIcs.ESA.2025.47,
  author =	{Haag, Manuel and Kurpicz, Florian and Sanders, Peter and Schimek, Matthias},
  title =	{{Fast and Lightweight Distributed Suffix Array Construction}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{47:1--47:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.47},
  URN =		{urn:nbn:de:0030-drops-245154},
  doi =		{10.4230/LIPIcs.ESA.2025.47},
  annote =	{Keywords: Distributed Computing, Suffix Array Construction}
}
Document
Invited Talk
DOI: 10.4230/LIPIcs.WABI.2025.2
We Are What We Index; a Primer for the Wheeler Graph Era (Invited Talk)

Authors: Ben Langmead

Published in: LIPIcs, Volume 344, 25th International Conference on Algorithms for Bioinformatics (WABI 2025)

Abstract
Since the arrival of second-generation sequencing, we have needed to build indexes over reference sequences - e.g. genomes and transcriptomes - in order to solve read alignment and classification problems efficiently [Langmead et al., 2009; Li and Durbin, 2009; Li et al., 2009]. The rule has been: what we can index determines what we can do. When indexing strings, we can use methods like suffix arrays [Manber and Myers, 1993], the Burrows-Wheeler Transform (BWT) [Burrows and Wheeler, 1994] / FM Index [Ferragina and Manzini, 2000], or k-mer indexes [Marchet et al., 2021]. What if we want to index objects more complex than strings? A pangenome, for example, is a large collection of similar strings, e.g. the hundreds of assemblies that make up the Human Pangenome Reference [Liao et al., 2023] or all the bacteria in the Refseq database [Goldfarb et al., 2025]. We may wish to combine these strings into a multiple sequence alignment (MSA) or a graph first. Can we index those efficiently? In many useful cases the answer is "yes," but in others the answer is "no." The story of how we learned exactly when the answer is "yes" versus "no" unfolded through a sequence of insights. Here we review this story, eventually arriving at the definition of Wheeler graphs as discovered and formalized by Gagie, Manzini and Sirén [Gagie et al., 2017]. We will focus on indexes based on the BWT, since these (a) are lossless full-text indexes, (b) are widely used in practice [Langmead et al., 2009; Li and Durbin, 2009], and (c) form the theoretical throughline for all the indexing strategies on the path to Wheeler graphs. We will trace the BWT-based indexing story from the early days of the FM Index, though its step-by-step gobbling up of trees (XBW-transform [Ferragina et al., 2005]) and de Bruijn Graphs (BOSS representation [Bowe et al., 2012]), and to the eventual formalization of Wheeler graphs [Gagie et al., 2017]. Along the way, we will define and update our notions of what it means to track a consecutive range of elements in the structure, and what it means for an index to be efficient. We will also connect these notions to automata [Sipser, 1996], noting how the indexability of Wheeler graphs (also called Wheeler automata) is connected to the mechanics of how to efficiently represent and simulate a finite automaton [Alanko et al., 2021]. With this context, we can imagine improved indexes for the future of genomics and pangenomics. De Bruijn are extremely practical and are the most widely used among the non-string data structures that are also Wheeler graphs. But we might prefer other options. For example, de Bruijn graphs have the undesirable property that they usually encode not only the true longer-than-k substrings of the original text, but also "false" substrings that span repeats. Related to this, paths through the de Bruijn graph can "glue" substrings together that are horizontally distant in the MSA. Could other Wheeler graphs be practical alternatives to de Bruijn graphs? For instance, the original GCSA study by Sirén, Välimäki and Mäkinen proposed a way to convert a multiple alignment into an automaton that either is a Wheeler graph or can be made into one [Sirén et al., 2014]. This warrants further exploration, possibly with the help of improved tools for solving the NP-complete problem of recognizing whether a graph is a Wheeler graph [Chao et al., 2023]. The notion of BWT tunnels [Baier, 2018] gives another route: we can begin with a concatenated pangenome strings and compress it by identifying and collapsing BWT tunnels. This yields a Wheeler graph that is compressed like the de Bruijn graph, but without departing from the exact contents or coordinate systems of the original genomes. The future might need us to explore all these Wheeler-graph indexes, along with the also highly practical and always-improving world of indexes buiover collections of strings [Gagie et al., 2018].
Cite as

Ben Langmead. We Are What We Index; a Primer for the Wheeler Graph Era (Invited Talk). In 25th International Conference on Algorithms for Bioinformatics (WABI 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 344, pp. 2:1-2:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{langmead:LIPIcs.WABI.2025.2,
  author =	{Langmead, Ben},
  title =	{{We Are What We Index; a Primer for the Wheeler Graph Era}},
  booktitle =	{25th International Conference on Algorithms for Bioinformatics (WABI 2025)},
  pages =	{2:1--2:2},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-386-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{344},
  editor =	{Brejov\'{a}, Bro\v{n}a and Patro, Rob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2025.2},
  URN =		{urn:nbn:de:0030-drops-239288},
  doi =		{10.4230/LIPIcs.WABI.2025.2},
  annote =	{Keywords: Indexing, Burrows-Wheeler Transform}
}
Document
Research
DOI: 10.4230/OASIcs.Grossi.13
Secure Compressed Suffix Arrays

Authors: Kunihiko Sadakane

Published in: OASIcs, Volume 132, From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday (2025)

Abstract
This paper proposes a secure compressed suffix array, which is a data oblivious and compressed version of the suffix array used for finding substrings of a large string. Secure compressed suffix arrays can be used for indexing a large collection of strings containing personal information such as DNA data.
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Kunihiko Sadakane. Secure Compressed Suffix Arrays. In From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 132, pp. 13:1-13:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{sadakane:OASIcs.Grossi.13,
  author =	{Sadakane, Kunihiko},
  title =	{{Secure Compressed Suffix Arrays}},
  booktitle =	{From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday},
  pages =	{13:1--13:8},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-391-1},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{132},
  editor =	{Conte, Alessio and Marino, Andrea and Rosone, Giovanna and Vitter, Jeffrey Scott},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Grossi.13},
  URN =		{urn:nbn:de:0030-drops-238122},
  doi =		{10.4230/OASIcs.Grossi.13},
  annote =	{Keywords: suffix array, compression, encryption, oblivious algorithm, secure computation}
}
Document
Research
DOI: 10.4230/OASIcs.Grossi.20
Subsequence-Based Indices for Genome Sequence Analysis

Authors: Giovanni Buzzega, Alessio Conte, Veronica Guerrini, Giulia Punzi, Giovanna Rosone, and Lorenzo Tattini

Published in: OASIcs, Volume 132, From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday (2025)

Abstract
Compact indices are a fundamental tool in string analysis, even more so in bioinformatics, where genomic sequences can reach billions in length. This paper presents some recent results in which Roberto Grossi has been involved, showing how some of these indices do more than just efficiently represent data, but rather are able to bring out salient information within it, which can be exploited for their downstream analysis. Specifically, we first review a recently-introduced method [Guerrini et al., 2023] that employs the Burrows-Wheeler Transform to build reasonably accurate phylogenetic trees in an assembly-free scenario. We then describe a recent practical tool [Buzzega et al., 2025] for indexing Maximal Common Subsequences between strings, which can enable analysis of genomic sequence similarity. Experimentally, we show that the results produced by the one index are consistent with the expectations about the results of the other index.
Cite as

Giovanni Buzzega, Alessio Conte, Veronica Guerrini, Giulia Punzi, Giovanna Rosone, and Lorenzo Tattini. Subsequence-Based Indices for Genome Sequence Analysis. In From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 132, pp. 20:1-20:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{buzzega_et_al:OASIcs.Grossi.20,
  author =	{Buzzega, Giovanni and Conte, Alessio and Guerrini, Veronica and Punzi, Giulia and Rosone, Giovanna and Tattini, Lorenzo},
  title =	{{Subsequence-Based Indices for Genome Sequence Analysis}},
  booktitle =	{From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday},
  pages =	{20:1--20:21},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-391-1},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{132},
  editor =	{Conte, Alessio and Marino, Andrea and Rosone, Giovanna and Vitter, Jeffrey Scott},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Grossi.20},
  URN =		{urn:nbn:de:0030-drops-238199},
  doi =		{10.4230/OASIcs.Grossi.20},
  annote =	{Keywords: String Indices, Burrows-Wheeler Transform, Maximal Common Subsequences, Sequence Analysis, Phylogeny}
}
Document
DOI: 10.4230/OASIcs.Manzini.5
FM-Adaptive: A Practical Data-Aware FM-Index

Authors: Hongwei Huo, Zongtao He, Pengfei Liu, and Jeffrey Scott Vitter

Published in: OASIcs, Volume 131, The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday (2025)

Abstract
The FM-index provides an important solution for efficient retrieval and search in textual big data. Its variants have been widely used in many fields including information retrieval, genome analysis, and web searching. In this paper, we propose improvements via a new compressed representation of the wavelet tree of the Burrows-Wheeler transform of the input text, which incorporates the gap γ-encoding. Our theoretical analysis shows that the new index, called FM-Adaptive, achieves asymptotic space optimality within a factor of 2 in the leading term, but it has a better compression and faster retrieval in practice than the competitive optimal compression boosting used in previous FM-indexes. We present a practical improved locate algorithm that provides substantially faster locating time based upon memoization, which takes advantage of the overlapping subproblems property. We design the lookup table for accelerated decoding to support fast pattern matching in a text. Extensive experiments demonstrate that FM-Adaptive provides faster query performance, often by a considerable amount, and/or comparable or better compression than other state-of-the-art FM-index methods.
Cite as

Hongwei Huo, Zongtao He, Pengfei Liu, and Jeffrey Scott Vitter. FM-Adaptive: A Practical Data-Aware FM-Index. In The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 131, pp. 5:1-5:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{huo_et_al:OASIcs.Manzini.5,
  author =	{Huo, Hongwei and He, Zongtao and Liu, Pengfei and Vitter, Jeffrey Scott},
  title =	{{FM-Adaptive: A Practical Data-Aware FM-Index}},
  booktitle =	{The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday},
  pages =	{5:1--5:23},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-390-4},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{131},
  editor =	{Ferragina, Paolo and Gagie, Travis and Navarro, Gonzalo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Manzini.5},
  URN =		{urn:nbn:de:0030-drops-239139},
  doi =		{10.4230/OASIcs.Manzini.5},
  annote =	{Keywords: Text indexing, Burrows-Wheeler transform, Compressed wavelet trees, Entropy-compressed, Compressed data structures}
}
Document
DOI: 10.4230/OASIcs.Manzini.6
Optimizing the Performance of the FM-Index for Large-Scale Data

Authors: Eddie Ferro and Christina Boucher

Published in: OASIcs, Volume 131, The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday (2025)

Abstract
The FM-index is a fundamental data structure used in bioinformatics to efficiently search for strings and index genomes. However, the FM-index can pose computational challenges, particularly in the context of large-scale genomic datasets, due to the complexity of its underlying components and data encodings. In this paper, we present a comprehensive review of efficient variants of the FM-index and the encoding strategies used to improve performance. We examine hardware-accelerated techniques, such as memory-efficient data layouts and cache-aware structures, as well as software-level innovations, including algorithmic refinements and compact representations. The reviewed work demonstrates substantial gains in both speed and scalability, making methods that use the FM-index more practical for high-throughput genomic applications. By analyzing the trade-offs and design choices of these variants, we highlight how combining hardware-aware and software-centric strategies enables more efficient FM-index construction and usage across a range of bioinformatics tasks.
Cite as

Eddie Ferro and Christina Boucher. Optimizing the Performance of the FM-Index for Large-Scale Data. In The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 131, pp. 6:1-6:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{ferro_et_al:OASIcs.Manzini.6,
  author =	{Ferro, Eddie and Boucher, Christina},
  title =	{{Optimizing the Performance of the FM-Index for Large-Scale Data}},
  booktitle =	{The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday},
  pages =	{6:1--6:21},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-390-4},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{131},
  editor =	{Ferragina, Paolo and Gagie, Travis and Navarro, Gonzalo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Manzini.6},
  URN =		{urn:nbn:de:0030-drops-239140},
  doi =		{10.4230/OASIcs.Manzini.6},
  annote =	{Keywords: FM-Index Acceleration, Run-Length Encoding, Suffix Array Optimization, Burrows-Wheeler Transform, Efficient Backward Search}
}
Document
DOI: 10.4230/OASIcs.Manzini.12
Wheeler Graphs and Wheeler Languages

Authors: Nicola Cotumaccio, Giovanna D'Agostino, Daniel Gibney, Alberto Policriti, Nicola Prezza, and Sharma V. Thankachan

Published in: OASIcs, Volume 131, The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday (2025)

Abstract
Suffix sorting stands at the core of the most efficient solutions for indexed pattern matching: the suffix tree, the suffix array, compressed indexes based on the Burrows-Wheeler transform, and so on. In [Gagie, Manzini, Sirén, TCS 2017] this concept was extended to labeled graphs, obtaining the rich class of Wheeler graphs. This work opened a very fruitful line of research, ultimately generating results able to bridge the fields of compressed data structures, graph theory, and regular language theory. In a Wheeler graph, nodes are sorted according to the alphabetic order of their incoming labels, propagating this order through pairs of equally-labeled edges. This apparently-simple definition makes it possible to solve on Wheeler graphs problems (including, but not limited to: compression, subpath queries, NFA equivalence, determinization, minimization) that on general labeled graphs are extremely hard to solve, and induces a rich structure in the class of regular languages (Wheeler languages) recognized by automata whose state transition is a Wheeler graph. The goal of this survey is to provide a summary of (and intuitions behind) the results on Wheeler graphs that appeared in the literature since their introduction, in addition to a discussion of interesting problems that are still open in the field.
Cite as

Nicola Cotumaccio, Giovanna D'Agostino, Daniel Gibney, Alberto Policriti, Nicola Prezza, and Sharma V. Thankachan. Wheeler Graphs and Wheeler Languages. In The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 131, pp. 12:1-12:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{cotumaccio_et_al:OASIcs.Manzini.12,
  author =	{Cotumaccio, Nicola and D'Agostino, Giovanna and Gibney, Daniel and Policriti, Alberto and Prezza, Nicola and Thankachan, Sharma V.},
  title =	{{Wheeler Graphs and Wheeler Languages}},
  booktitle =	{The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday},
  pages =	{12:1--12:28},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-390-4},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{131},
  editor =	{Ferragina, Paolo and Gagie, Travis and Navarro, Gonzalo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Manzini.12},
  URN =		{urn:nbn:de:0030-drops-239205},
  doi =		{10.4230/OASIcs.Manzini.12},
  annote =	{Keywords: Wheeler languages, Wheeler graphs, pattern matching, indexing, compressed data structures}
}
Document
DOI: 10.4230/OASIcs.Manzini.9
Search Schemes for Approximate Pattern Matching: An Overview

Authors: Lore Depuydt, Jan Fostier, Simon Gottlieb, Gregory Kucherov, Knut Reinert, and Luca Renders

Published in: OASIcs, Volume 131, The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday (2025)

Abstract
We provide a brief survey of results on solving the approximate pattern matching problem using search schemes, as introduced by Kucherov et al. (2016). We demonstrate that search schemes constitute a flexible and versatile tool that enable the specification of various search strategies, including several known filtering methods. We present approaches for designing efficient search schemes and for implementing them effectively. Finally, we conclude with experimental results comparing multiple search schemes on DNA sequencing data using the Columba software by Renders et al. (2021).
Cite as

Lore Depuydt, Jan Fostier, Simon Gottlieb, Gregory Kucherov, Knut Reinert, and Luca Renders. Search Schemes for Approximate Pattern Matching: An Overview. In The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 131, pp. 9:1-9:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{depuydt_et_al:OASIcs.Manzini.9,
  author =	{Depuydt, Lore and Fostier, Jan and Gottlieb, Simon and Kucherov, Gregory and Reinert, Knut and Renders, Luca},
  title =	{{Search Schemes for Approximate Pattern Matching: An Overview}},
  booktitle =	{The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday},
  pages =	{9:1--9:16},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-390-4},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{131},
  editor =	{Ferragina, Paolo and Gagie, Travis and Navarro, Gonzalo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Manzini.9},
  URN =		{urn:nbn:de:0030-drops-239172},
  doi =		{10.4230/OASIcs.Manzini.9},
  annote =	{Keywords: FM-index, bidirectional index, approximate pattern matching, search scheme}
}
Document
DOI: 10.4230/LIPIcs.SEA.2025.13
Pangenome Graph Indexing via the Multidollar-BWT

Authors: Davide Cozzi, Brian Riccardi, Luca Denti, Simone Ciccolella, Kunihiko Sadakane, and Paola Bonizzoni

Published in: LIPIcs, Volume 338, 23rd International Symposium on Experimental Algorithms (SEA 2025)

Abstract
Indexing pangenome graphs is a major algorithmic challenge in computational pangenomics, a recent and active research field that seeks to use graphs as representations of multiple genomes. Since these graphs are constructed from whole genome sequences of a species population, they can become very large, making indexing one of the most challenging problems. In this paper, we propose gindex, a novel indexing approach to solve the Graph Pattern Matching Problem based on the multidollar-BWT. Specifically, gindex aims to find all occurrences of a pattern in a sequence-labeled graph by overcoming two main limitations of GCSA2, one of the most widely used graph indexes: handling queries of arbitrary length and scaling to large graphs without pruning any complex regions. Moreover, we show how a smart preprocessing step can optimize the use of multidollar-BWT to skip small redundant sub-patterns and enhance gindex’s querying capabilities. We demonstrate the effectiveness of our approach by comparing it to GCSA2 in terms of index construction and query time, using different preprocessing modes on three pangenome graphs: one built from Drosophila genomes and two produced by the Human Pangenome Reference Consortium. The results show that gindex can scale on human pangenome graphs - which GCSA2 cannot index using large amounts of RAM - with acceptable memory and time requirements. Moreover, gindex achieves fast query times, although not as fast as GCSA2, which may produce false positives.
Cite as

Davide Cozzi, Brian Riccardi, Luca Denti, Simone Ciccolella, Kunihiko Sadakane, and Paola Bonizzoni. Pangenome Graph Indexing via the Multidollar-BWT. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 13:1-13:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{cozzi_et_al:LIPIcs.SEA.2025.13,
  author =	{Cozzi, Davide and Riccardi, Brian and Denti, Luca and Ciccolella, Simone and Sadakane, Kunihiko and Bonizzoni, Paola},
  title =	{{Pangenome Graph Indexing via the Multidollar-BWT}},
  booktitle =	{23rd International Symposium on Experimental Algorithms (SEA 2025)},
  pages =	{13:1--13:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-375-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{338},
  editor =	{Mutzel, Petra and Prezza, Nicola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.13},
  URN =		{urn:nbn:de:0030-drops-232515},
  doi =		{10.4230/LIPIcs.SEA.2025.13},
  annote =	{Keywords: Multidollar-BWT, Graph Index, Graph Pattern Matching, Pangenome Graph}
}
Document
DOI: 10.4230/LIPIcs.CPM.2025.12
Shortest Undirected Paths in de Bruijn Graphs

Authors: Wiktor Zuba, Oded Lachish, and Solon P. Pissis

Published in: LIPIcs, Volume 331, 36th Annual Symposium on Combinatorial Pattern Matching (CPM 2025)

Abstract
Computing shortest directed paths in de Bruijn graphs is well studied and well understood. This is not the case for computing undirected paths, which is much more challenging algorithmically. In this paper, we present a general framework for computing shortest undirected paths in arbitrary de Bruijn graphs, that is, arbitrary subgraphs of the complete de Bruijn graph. We then present an application of our techniques for making any arbitrary order-k de Bruijn graph G(V,E) weakly connected by adding a set of edges of minimum total cost. This improves the running time of the recent (2-2/d)-approximation algorithm by Bernardini et al. [CPM 2024] from 𝒪(k|V|²) to 𝒪(k|V|log d) time, where d is the number of weakly connected components of graph G.
Cite as

Wiktor Zuba, Oded Lachish, and Solon P. Pissis. Shortest Undirected Paths in de Bruijn Graphs. In 36th Annual Symposium on Combinatorial Pattern Matching (CPM 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 331, pp. 12:1-12:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{zuba_et_al:LIPIcs.CPM.2025.12,
  author =	{Zuba, Wiktor and Lachish, Oded and Pissis, Solon P.},
  title =	{{Shortest Undirected Paths in de Bruijn Graphs}},
  booktitle =	{36th Annual Symposium on Combinatorial Pattern Matching (CPM 2025)},
  pages =	{12:1--12:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-369-0},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{331},
  editor =	{Bonizzoni, Paola and M\"{a}kinen, Veli},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2025.12},
  URN =		{urn:nbn:de:0030-drops-231060},
  doi =		{10.4230/LIPIcs.CPM.2025.12},
  annote =	{Keywords: string algorithm, graph algorithm, de Bruijn graph, Eulerian graph}
}
Document
DOI: 10.4230/OASIcs.Tannen.6
Fishing Fort: A System for Graph Analytics with ML Prediction and Logic Deduction

Authors: Wenfei Fan and Shuhao Liu

Published in: OASIcs, Volume 119, The Provenance of Elegance in Computation - Essays Dedicated to Val Tannen (2024)

Abstract
This paper reports Fishing Fort, a graph analytic system developed in response to the following questions. What practical value can we get out of graph analytics? How can we effectively deduce the value from a real-life graph? Where can we get clean graphs to make accurate analyses possible? To answer these questions, Fishing Fort advocates to unify logic deduction and ML prediction by proposing Graph Association Rules (GARs), a class of logic rules in which ML models can be embedded as predicates. It employs GARs to deduce graph associations, enrich graphs and clean graphs. It has been deployed in production lines and proven effective in online recommendation, drug discovery, credit risk assessment, battery manufacturing and cybersecurity, among other things.
Cite as

Wenfei Fan and Shuhao Liu. Fishing Fort: A System for Graph Analytics with ML Prediction and Logic Deduction. In The Provenance of Elegance in Computation - Essays Dedicated to Val Tannen. Open Access Series in Informatics (OASIcs), Volume 119, pp. 6:1-6:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{fan_et_al:OASIcs.Tannen.6,
  author =	{Fan, Wenfei and Liu, Shuhao},
  title =	{{Fishing Fort: A System for Graph Analytics with ML Prediction and Logic Deduction}},
  booktitle =	{The Provenance of Elegance in Computation - Essays Dedicated to Val Tannen},
  pages =	{6:1--6:18},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-320-1},
  ISSN =	{2190-6807},
  year =	{2024},
  volume =	{119},
  editor =	{Amarilli, Antoine and Deutsch, Alin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Tannen.6},
  URN =		{urn:nbn:de:0030-drops-201025},
  doi =		{10.4230/OASIcs.Tannen.6},
  annote =	{Keywords: graph analytics, data cleaning, association analysis}
}
Document
DOI: 10.4230/LIPIcs.CPM.2023.22
Merging Sorted Lists of Similar Strings

Authors: Gene Myers

Published in: LIPIcs, Volume 259, 34th Annual Symposium on Combinatorial Pattern Matching (CPM 2023)

Abstract
Merging T sorted, non-redundant lists containing M elements into a single sorted, non-redundant result of size N ≥ M/T is a classic problem typically solved practically in O(M log T) time with a priority-queue data structure the most basic of which is the simple heap. We revisit this problem in the situation where the list elements are strings and the lists contain many identical or nearly identical elements. By keeping simple auxiliary information with each heap node, we devise an O(M log T+S) worst-case method that performs no more character comparisons than the sum of the lengths of all the strings S, and another O(M log (T/e¯)+S) method that becomes progressively more efficient as a function of the fraction of equal elements e¯ = M/N between input lists, reaching linear time when the lists are all identical. The methods perform favorably in practice versus an alternate formulation based on a trie.
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Gene Myers. Merging Sorted Lists of Similar Strings. In 34th Annual Symposium on Combinatorial Pattern Matching (CPM 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 259, pp. 22:1-22:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{myers:LIPIcs.CPM.2023.22,
  author =	{Myers, Gene},
  title =	{{Merging Sorted Lists of Similar Strings}},
  booktitle =	{34th Annual Symposium on Combinatorial Pattern Matching (CPM 2023)},
  pages =	{22:1--22:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-276-1},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{259},
  editor =	{Bulteau, Laurent and Lipt\'{a}k, Zsuzsanna},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2023.22},
  URN =		{urn:nbn:de:0030-drops-179763},
  doi =		{10.4230/LIPIcs.CPM.2023.22},
  annote =	{Keywords: heap, trie, longest common prefix}
}
Document
DOI: 10.4230/LIPIcs.WABI.2022.10
Accurate k-mer Classification Using Read Profiles

Authors: Yoshihiko Suzuki and Gene Myers

Published in: LIPIcs, Volume 242, 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022)

Abstract
Contiguous strings of length k, called k-mers, are a fundamental element in many bioinformatics tasks. The number of occurrences of a k-mer in a given set of DNA sequencing reads, its k-mer count, has often been used to roughly estimate the copy number of a k-mer in the genome from which the reads were sampled. The problem of estimating copy numbers, called here the k-mer classification problem, has been based on simply analyzing the histogram of counts of all the k-mers in a data set, thus ignoring the positional context and dependency between multiple k-mers that appear nearby in the underlying genome. Here we present an efficient and significantly more accurate method for classifying k-mers by analyzing the sequence of k-mer counts along each sequencing read, called a read profile. By analyzing read profiles, we explicitly incorporate into the model the dependencies between the positionally adjacent k-mers and the sequence context-dependent error rates estimated from the given dataset. For long sequencing reads produced with the accurate high-fidelity (HiFi) sequencing technology, an implementation of our method, ClassPro, outperforms the conventional, histogram-based method in every simulation dataset of fruit fly and human with various realistic values of sequencing coverage and heterozygosity. Within only a few minutes, ClassPro achieves an average accuracy of > 99.99% across reads without repetitive k-mers and > 99.5% across all reads, in a typical fruit fly simulation data set with a 40× coverage. The resulting, more accurate k-mer classifications by ClassPro are in principle expected to improve any k-mer-based downstream analyses for sequenced reads such as read mapping and overlap, spectral alignment and error correction, haplotype phasing, and trio binning to name but a few. ClassPro is available at https://github.com/yoshihikosuzuki/ClassPro.
Cite as

Yoshihiko Suzuki and Gene Myers. Accurate k-mer Classification Using Read Profiles. In 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 242, pp. 10:1-10:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{suzuki_et_al:LIPIcs.WABI.2022.10,
  author =	{Suzuki, Yoshihiko and Myers, Gene},
  title =	{{Accurate k-mer Classification Using Read Profiles}},
  booktitle =	{22nd International Workshop on Algorithms in Bioinformatics (WABI 2022)},
  pages =	{10:1--10:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-243-3},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{242},
  editor =	{Boucher, Christina and Rahmann, Sven},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2022.10},
  URN =		{urn:nbn:de:0030-drops-170446},
  doi =		{10.4230/LIPIcs.WABI.2022.10},
  annote =	{Keywords: K-mer, K-mer count, K-mer classification, HiFi sequencing}
}
Document
DOI: 10.4230/LIPIcs.CPM.2019.10
Fully-Functional Bidirectional Burrows-Wheeler Indexes and Infinite-Order De Bruijn Graphs

Authors: Djamal Belazzougui and Fabio Cunial

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

Abstract
Given a string T on an alphabet of size sigma, we describe a bidirectional Burrows-Wheeler index that takes O(|T| log sigma) bits of space, and that supports the addition and removal of one character, on the left or right side of any substring of T, in constant time. Previously known data structures that used the same space allowed constant-time addition to any substring of T, but they could support removal only from specific substrings of T. We also describe an index that supports bidirectional addition and removal in O(log log |T|) time, and that takes a number of words proportional to the number of left and right extensions of the maximal repeats of T. We use such fully-functional indexes to implement bidirectional, frequency-aware, variable-order de Bruijn graphs with no upper bound on their order, and supporting natural criteria for increasing and decreasing the order during traversal.
Cite as

Djamal Belazzougui and Fabio Cunial. Fully-Functional Bidirectional Burrows-Wheeler Indexes and Infinite-Order De Bruijn Graphs. In 30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 128, pp. 10:1-10:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{belazzougui_et_al:LIPIcs.CPM.2019.10,
  author =	{Belazzougui, Djamal and Cunial, Fabio},
  title =	{{Fully-Functional Bidirectional Burrows-Wheeler Indexes and Infinite-Order De Bruijn Graphs}},
  booktitle =	{30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019)},
  pages =	{10:1--10:15},
  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.2019.10},
  URN =		{urn:nbn:de:0030-drops-104811},
  doi =		{10.4230/LIPIcs.CPM.2019.10},
  annote =	{Keywords: BWT, suffix tree, CDAWG, de Bruijn graph, maximal repeat, string depth, contraction, bidirectional index}
}
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