165 Search Results for "Navarro, Gonzalo"

Volume

LIPIcs, Volume 244

30th Annual European Symposium on Algorithms (ESA 2022)

ESA 2022, September 5-9, 2022, Berlin/Potsdam, Germany

Editors: Shiri Chechik, Gonzalo Navarro, Eva Rotenberg, and Grzegorz Herman

Volume

LIPIcs, Volume 105

29th Annual Symposium on Combinatorial Pattern Matching (CPM 2018)

CPM 2018, July 2-4, 2018, Qingdao, China

Editors: Gonzalo Navarro, David Sankoff, and Binhai Zhu

Document
DOI: 10.4230/LIPIcs.WABI.2024.10
b-move: Faster Bidirectional Character Extensions in a Run-Length Compressed Index

Authors: Lore Depuydt, Luca Renders, Simon Van de Vyver, Lennart Veys, Travis Gagie, and Jan Fostier

Published in: LIPIcs, Volume 312, 24th International Workshop on Algorithms in Bioinformatics (WABI 2024)

Abstract
Due to the increasing availability of high-quality genome sequences, pan-genomes are gradually replacing single consensus reference genomes in many bioinformatics pipelines to better capture genetic diversity. Traditional bioinformatics tools using the FM-index face memory limitations with such large genome collections. Recent advancements in run-length compressed indices like Gagie et al.’s r-index and Nishimoto and Tabei’s move structure, alleviate memory constraints but focus primarily on backward search for MEM-finding. Arakawa et al.’s br-index initiates complete approximate pattern matching using bidirectional search in run-length compressed space, but with significant computational overhead due to complex memory access patterns. We introduce b-move, a novel bidirectional extension of the move structure, enabling fast, cache-efficient bidirectional character extensions in run-length compressed space. It achieves bidirectional character extensions up to 8 times faster than the br-index, closing the performance gap with FM-index-based alternatives, while maintaining the br-index’s favorable memory characteristics. For example, all available complete E. coli genomes on NCBI’s RefSeq collection can be compiled into a b-move index that fits into the RAM of a typical laptop. Thus, b-move proves practical and scalable for pan-genome indexing and querying. We provide a C++ implementation of b-move, supporting efficient lossless approximate pattern matching including locate functionality, available at https://github.com/biointec/b-move under the AGPL-3.0 license.
Cite as

Lore Depuydt, Luca Renders, Simon Van de Vyver, Lennart Veys, Travis Gagie, and Jan Fostier. b-move: Faster Bidirectional Character Extensions in a Run-Length Compressed Index. In 24th International Workshop on Algorithms in Bioinformatics (WABI 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 312, pp. 10:1-10:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{depuydt_et_al:LIPIcs.WABI.2024.10,
  author =	{Depuydt, Lore and Renders, Luca and Van de Vyver, Simon and Veys, Lennart and Gagie, Travis and Fostier, Jan},
  title =	{{b-move: Faster Bidirectional Character Extensions in a Run-Length Compressed Index}},
  booktitle =	{24th International Workshop on Algorithms in Bioinformatics (WABI 2024)},
  pages =	{10:1--10:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-340-9},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{312},
  editor =	{Pissis, Solon P. and Sung, Wing-Kin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2024.10},
  URN =		{urn:nbn:de:0030-drops-206546},
  doi =		{10.4230/LIPIcs.WABI.2024.10},
  annote =	{Keywords: Pan-genomics, FM-index, r-index, Move Structure, Bidirectional Search, Approximate Pattern Matching, Lossless Alignment, Cache Efficiency}
}
Document
DOI: 10.4230/LIPIcs.WABI.2024.13
PLA-index: A k-mer Index Exploiting Rank Curve Linearity

Authors: Md. Hasin Abrar and Paul Medvedev

Published in: LIPIcs, Volume 312, 24th International Workshop on Algorithms in Bioinformatics (WABI 2024)

Abstract
Given a sorted list of k-mers S, the rank curve of S is the function mapping a k-mer from the k-mer universe to the location in S where it either first appears or would be inserted. An exciting recent development is the observation that, for certain datasets, the rank curve is predictable and can be exploited to create small search indices. In this paper, we develop a novel search index that first estimates a k-mer’s rank using a piece-wise linear approximation of the rank curve and then does a local search to determine the precise location of the k-mer in the list. We combine ideas from previous approaches and supplement them with an innovative data representation strategy that substantially reduces space usage. Our PLA-index uses an order of magnitude less space than Sapling and uses less than half the space of the PGM-index, for roughly the same query time. For example, using only 9 MiB of memory, it can narrow down the position of k-mer in the suffix array of the human genome to within 255 positions. Furthermore, we demonstrate the potential of our approach to impact a variety of downstream applications. First, the PLA-index halves the time of binary search on the suffix array of the human genome. Second, the PLA-index reduces the space of a direct-access lookup table by 76 percent, without increasing the run time. Third, we plug the PLA-index into a state-of-the-art read aligner Strobealign and replace a 2 GiB component with a PLA-index of size 1.5 MiB, without significantly effecting runtime. The software and reproducibility information is freely available at https://github.com/medvedevgroup/pla-index.
Cite as

Md. Hasin Abrar and Paul Medvedev. PLA-index: A k-mer Index Exploiting Rank Curve Linearity. In 24th International Workshop on Algorithms in Bioinformatics (WABI 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 312, pp. 13:1-13:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{abrar_et_al:LIPIcs.WABI.2024.13,
  author =	{Abrar, Md. Hasin and Medvedev, Paul},
  title =	{{PLA-index: A k-mer Index Exploiting Rank Curve Linearity}},
  booktitle =	{24th International Workshop on Algorithms in Bioinformatics (WABI 2024)},
  pages =	{13:1--13:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-340-9},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{312},
  editor =	{Pissis, Solon P. and Sung, Wing-Kin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2024.13},
  URN =		{urn:nbn:de:0030-drops-206578},
  doi =		{10.4230/LIPIcs.WABI.2024.13},
  annote =	{Keywords: K-mer index, Piece-wise linear approximation, Learned index}
}
Document
DOI: 10.4230/LIPIcs.WABI.2024.17
A*PA2: Up to 19× Faster Exact Global Alignment

Authors: Ragnar Groot Koerkamp

Published in: LIPIcs, Volume 312, 24th International Workshop on Algorithms in Bioinformatics (WABI 2024)

Abstract
Motivation. Pairwise alignment is at the core of computational biology. Most commonly used exact methods are either based on O(ns) band doubling or O(n+s²) diagonal transition, where n is the sequence length and s the number of errors. However, as the length of sequences has grown, these exact methods are often replaced by approximate methods based on e.g. seed-and-extend and heuristics to bound the computed region. We would like to develop an exact method that matches the performance of these approximate methods. Recently, Astarix introduced the A* shortest path algorithm with the seed heuristic for exact sequence-to-graph alignment. A*PA adapted and improved this for pairwise sequence alignment and achieves near-linear runtime when divergence (error rate) is low, at the cost of being very slow when divergence is high. Methods. We introduce A*PA2, an exact global pairwise aligner with respect to edit distance. The goal of A*PA2 is to unify the near-linear runtime of A*PA on similar sequences with the efficiency of dynamic programming (DP) based methods. Like Edlib, A*PA2 uses Ukkonen’s band doubling in combination with Myers' bitpacking. A*PA2 1) uses large block sizes inspired by Block Aligner, 2) extends this with SIMD (single instruction, multiple data), 3) introduces a new profile for efficient computations, 4) introduces a new optimistic technique for traceback based on diagonal transition, 5) avoids recomputation of states where possible, and 6) applies the heuristics developed in A*PA and improves them using pre-pruning. Results. With the first 4 engineering optimizations, A*PA2-simple has complexity O(ns) and is 6× to 8× faster than Edlib for sequences ≥ 10 kbp. A*PA2-full also includes the heuristic and is often near-linear in practice for sequences with small divergence. The average runtime of A*PA2 is 19× faster than the exact aligners BiWFA and Edlib on >500 kbp long ONT (Oxford Nanopore Technologies) reads of a human genome having 6% divergence on average. On shorter ONT reads of 11% average divergence the speedup is 5.6× (avg. length 11 kbp) and 0.81× (avg. length 800 bp). On all tested datasets, A*PA2 is competitive with or faster than approximate methods.
Cite as

Ragnar Groot Koerkamp. A*PA2: Up to 19× Faster Exact Global Alignment. In 24th International Workshop on Algorithms in Bioinformatics (WABI 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 312, pp. 17:1-17:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{grootkoerkamp:LIPIcs.WABI.2024.17,
  author =	{Groot Koerkamp, Ragnar},
  title =	{{A*PA2: Up to 19× Faster Exact Global Alignment}},
  booktitle =	{24th International Workshop on Algorithms in Bioinformatics (WABI 2024)},
  pages =	{17:1--17:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-340-9},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{312},
  editor =	{Pissis, Solon P. and Sung, Wing-Kin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2024.17},
  URN =		{urn:nbn:de:0030-drops-206610},
  doi =		{10.4230/LIPIcs.WABI.2024.17},
  annote =	{Keywords: Edit distance, Pairwise alignment, A*, Shortest path, Dynamic programming}
}
Document
DOI: 10.4230/LIPIcs.MFCS.2024.22
Graph Search Trees and the Intermezzo Problem

Authors: Jesse Beisegel, Ekkehard Köhler, Fabienne Ratajczak, Robert Scheffler, and Martin Strehler

Published in: LIPIcs, Volume 306, 49th International Symposium on Mathematical Foundations of Computer Science (MFCS 2024)

Abstract
The last in-tree recognition problem asks whether a given spanning tree can be derived by connecting each vertex with its rightmost left neighbor of some search ordering. In this study, we demonstrate that the last-in-tree recognition problem for Generic Search is NP-complete. We utilize this finding to strengthen a complexity result from order theory. Given a partial order π and a set of triples, the NP-complete intermezzo problem asks for a linear extension of π where each first element of a triple is not between the other two. We show that this problem remains NP-complete even when the Hasse diagram of the partial order forms a tree of bounded height. In contrast, we give an XP-algorithm for the problem when parameterized by the width of the partial order. Furthermore, we show that - under the assumption of the Exponential Time Hypothesis - the running time of this algorithm is asymptotically optimal.
Cite as

Jesse Beisegel, Ekkehard Köhler, Fabienne Ratajczak, Robert Scheffler, and Martin Strehler. Graph Search Trees and the Intermezzo Problem. In 49th International Symposium on Mathematical Foundations of Computer Science (MFCS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 306, pp. 22:1-22:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{beisegel_et_al:LIPIcs.MFCS.2024.22,
  author =	{Beisegel, Jesse and K\"{o}hler, Ekkehard and Ratajczak, Fabienne and Scheffler, Robert and Strehler, Martin},
  title =	{{Graph Search Trees and the Intermezzo Problem}},
  booktitle =	{49th International Symposium on Mathematical Foundations of Computer Science (MFCS 2024)},
  pages =	{22:1--22:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-335-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{306},
  editor =	{Kr\'{a}lovi\v{c}, Rastislav and Ku\v{c}era, Anton{\'\i}n},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2024.22},
  URN =		{urn:nbn:de:0030-drops-205781},
  doi =		{10.4230/LIPIcs.MFCS.2024.22},
  annote =	{Keywords: graph search trees, intermezzo problem, algorithm, parameterized complexity}
}
Document
DOI: 10.4230/LIPIcs.MFCS.2024.75
Edit and Alphabet-Ordering Sensitivity of Lex-Parse

Authors: Yuto Nakashima, Dominik Köppl, Mitsuru Funakoshi, Shunsuke Inenaga, and Hideo Bannai

Published in: LIPIcs, Volume 306, 49th International Symposium on Mathematical Foundations of Computer Science (MFCS 2024)

Abstract
We investigate the compression sensitivity [Akagi et al., 2023] of lex-parse [Navarro et al., 2021] for two operations: (1) single character edit and (2) modification of the alphabet ordering, and give tight upper and lower bounds for both operations (i.e., we show Θ(log n) bounds for strings of length n). For both lower bounds, we use the family of Fibonacci words. For the bounds on edit operations, our analysis makes heavy use of properties of the Lyndon factorization of Fibonacci words to characterize the structure of lex-parse.
Cite as

Yuto Nakashima, Dominik Köppl, Mitsuru Funakoshi, Shunsuke Inenaga, and Hideo Bannai. Edit and Alphabet-Ordering Sensitivity of Lex-Parse. In 49th International Symposium on Mathematical Foundations of Computer Science (MFCS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 306, pp. 75:1-75:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{nakashima_et_al:LIPIcs.MFCS.2024.75,
  author =	{Nakashima, Yuto and K\"{o}ppl, Dominik and Funakoshi, Mitsuru and Inenaga, Shunsuke and Bannai, Hideo},
  title =	{{Edit and Alphabet-Ordering Sensitivity of Lex-Parse}},
  booktitle =	{49th International Symposium on Mathematical Foundations of Computer Science (MFCS 2024)},
  pages =	{75:1--75:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-335-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{306},
  editor =	{Kr\'{a}lovi\v{c}, Rastislav and Ku\v{c}era, Anton{\'\i}n},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2024.75},
  URN =		{urn:nbn:de:0030-drops-206314},
  doi =		{10.4230/LIPIcs.MFCS.2024.75},
  annote =	{Keywords: Compression sensitivity, Lex-parse, Fibonacci words}
}
Document
DOI: 10.4230/LIPIcs.MFCS.2024.85
Approximate Suffix-Prefix Dictionary Queries

Authors: Wiktor Zuba, Grigorios Loukides, Solon P. Pissis, and Sharma V. Thankachan

Published in: LIPIcs, Volume 306, 49th International Symposium on Mathematical Foundations of Computer Science (MFCS 2024)

Abstract
In the all-pairs suffix-prefix (APSP) problem [Gusfield et al., Inf. Process. Lett. 1992], we are given a dictionary R of r strings, S₁,…,S_r, of total length n, and we are asked to find the length SPL_{i,j} of the longest string that is both a suffix of S_i and a prefix of S_j, for all i,j ∈ [1..r]. APSP is a classic problem in string algorithms with applications in bioinformatics, especially in sequence assembly. Since r = |R| is typically very large in real-world applications, considering all r² pairs of strings explicitly is prohibitive. This is when the data structure variant of APSP makes sense; in the same spirit as distance oracles computing shortest paths between any two vertices given online. We show how to quickly locate k-approximate matches (under the Hamming or the edit distance) in R using a version of the k-errata tree [Cole et al., STOC 2004] that we introduce. Let SPL^k_{i,j} be the length of the longest suffix of S_i that is at distance at most k from a prefix of S_j. In particular, for any k = 𝒪(1), we show an 𝒪(nlog^k n)-sized data structure to support the following queries: - One-to-One^k(i,j): output SPL^k_{i,j} in 𝒪(log^k nlog log n) time. - Report^k(i,d): output all j ∈ [1..r], such that SPL^k_{i,j} ≥ d, in 𝒪(log^{k}n(log n/log log n+output)) time, where output denotes the size of the output. In fact, our algorithms work for any value of k not just for k = 𝒪(1), but the formulas bounding the complexities get much more complicated for larger values of k.
Cite as

Wiktor Zuba, Grigorios Loukides, Solon P. Pissis, and Sharma V. Thankachan. Approximate Suffix-Prefix Dictionary Queries. In 49th International Symposium on Mathematical Foundations of Computer Science (MFCS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 306, pp. 85:1-85:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{zuba_et_al:LIPIcs.MFCS.2024.85,
  author =	{Zuba, Wiktor and Loukides, Grigorios and Pissis, Solon P. and Thankachan, Sharma V.},
  title =	{{Approximate Suffix-Prefix Dictionary Queries}},
  booktitle =	{49th International Symposium on Mathematical Foundations of Computer Science (MFCS 2024)},
  pages =	{85:1--85:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-335-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{306},
  editor =	{Kr\'{a}lovi\v{c}, Rastislav and Ku\v{c}era, Anton{\'\i}n},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2024.85},
  URN =		{urn:nbn:de:0030-drops-206416},
  doi =		{10.4230/LIPIcs.MFCS.2024.85},
  annote =	{Keywords: all-pairs suffix-prefix, suffix-prefix queries, suffix tree, k-errata tree}
}
Document
DOI: 10.4230/LIPIcs.AofA.2024.2
Enumeration and Succinct Encoding of AVL Trees

Authors: Jeremy Chizewer, Stephen Melczer, J. Ian Munro, and Ava Pun

Published in: LIPIcs, Volume 302, 35th International Conference on Probabilistic, Combinatorial and Asymptotic Methods for the Analysis of Algorithms (AofA 2024)

Abstract
We use a novel decomposition to create succinct data structures - supporting a wide range of operations on static trees in constant time - for a variety of tree classes, extending results of Munro, Nicholson, Benkner, and Wild. Motivated by the class of AVL trees, we further derive asymptotics for the information-theoretic lower bound on the number of bits needed to store tree classes whose generating functions satisfy certain functional equations. In particular, we prove that AVL trees require approximately 0.938 bits per node to encode.
Cite as

Jeremy Chizewer, Stephen Melczer, J. Ian Munro, and Ava Pun. Enumeration and Succinct Encoding of AVL Trees. In 35th International Conference on Probabilistic, Combinatorial and Asymptotic Methods for the Analysis of Algorithms (AofA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 302, pp. 2:1-2:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{chizewer_et_al:LIPIcs.AofA.2024.2,
  author =	{Chizewer, Jeremy and Melczer, Stephen and Munro, J. Ian and Pun, Ava},
  title =	{{Enumeration and Succinct Encoding of AVL Trees}},
  booktitle =	{35th International Conference on Probabilistic, Combinatorial and Asymptotic Methods for the Analysis of Algorithms (AofA 2024)},
  pages =	{2:1--2:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-329-4},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{302},
  editor =	{Mailler, C\'{e}cile and Wild, Sebastian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.AofA.2024.2},
  URN =		{urn:nbn:de:0030-drops-204376},
  doi =		{10.4230/LIPIcs.AofA.2024.2},
  annote =	{Keywords: AVL trees, analytic combinatorics, succinct data structures, enumeration}
}
Document
DOI: 10.4230/LIPIcs.SEA.2024.1
Move-r: Optimizing the r-index

Authors: Nico Bertram, Johannes Fischer, and Lukas Nalbach

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

Abstract
We present a static text index called Move-r, which is a highly optimized version of the r-index ([Travis Gagie et al., 2020] Gagie et al., 2020) that encorporates recent theoretical developments of the move data structure ([Takaaki Nishimoto and Yasuo Tabei, 2021] Nishimoto and Tabei, 2021). The r-index is the method of choice for indexing highly repetitive texts, such as different versions of a text document or DNA from the same species, as it exploits the compressibilty of the underlying data. With Move-r, we can answer count- and locate queries 2-35 (typically 15) times as fast as with any other r-index supporting locate queries while being 0.8-2.5 (typically 2) times as large. A Move-r index can be constructed 0.9-2 (typically 2) times as fast while using 1/3-1 (typically 1/2) times as much space.
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Nico Bertram, Johannes Fischer, and Lukas Nalbach. Move-r: Optimizing the r-index. In 22nd International Symposium on Experimental Algorithms (SEA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 301, pp. 1:1-1:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{bertram_et_al:LIPIcs.SEA.2024.1,
  author =	{Bertram, Nico and Fischer, Johannes and Nalbach, Lukas},
  title =	{{Move-r: Optimizing the r-index}},
  booktitle =	{22nd International Symposium on Experimental Algorithms (SEA 2024)},
  pages =	{1:1--1:19},
  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.2024.1},
  URN =		{urn:nbn:de:0030-drops-203662},
  doi =		{10.4230/LIPIcs.SEA.2024.1},
  annote =	{Keywords: Compressed Text Index, Burrows-Wheeler Transform}
}
Document
DOI: 10.4230/LIPIcs.SEA.2024.2
Engineering Zuffix Arrays

Authors: Paolo Boldi, Stefano Marchini, and Sebastiano Vigna

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

Abstract
Searching patterns in long strings is a classical algorithmic problem with countless practical applications. Suffix trees and suffix arrays (and their variants) are a long-established solution that yields linear-time search (in the size of the pattern). In [Paolo Boldi and Sebastiano Vigna, 2018] it is shown that a z-map gadget can be attached to (enhanced) suffix arrays to improve their theoretical query time, obtaining a data structure called zuffix array. The main contribution of this paper is to show that a carefully engineered implementation of the z-map gadget does provide significant speedups with respect to enhanced suffix arrays on real-world datasets, albeit doubling the required space. In particular, for large alphabets we observe a sevenfold improvement in query time with respect to enhanced suffix arrays; even in the worst case (small alphabets), the query time is almost halved. Thus, zuffix arrays provide a very interesting new point in the space-time tradeoff spectrum.
Cite as

Paolo Boldi, Stefano Marchini, and Sebastiano Vigna. Engineering Zuffix Arrays. In 22nd International Symposium on Experimental Algorithms (SEA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 301, pp. 2:1-2:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{boldi_et_al:LIPIcs.SEA.2024.2,
  author =	{Boldi, Paolo and Marchini, Stefano and Vigna, Sebastiano},
  title =	{{Engineering Zuffix Arrays}},
  booktitle =	{22nd International Symposium on Experimental Algorithms (SEA 2024)},
  pages =	{2:1--2:18},
  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.2024.2},
  URN =		{urn:nbn:de:0030-drops-203677},
  doi =		{10.4230/LIPIcs.SEA.2024.2},
  annote =	{Keywords: Suffix trees, suffix arrays, z-fast tries}
}
Document
DOI: 10.4230/LIPIcs.SEA.2024.10
Taxonomic Classification with Maximal Exact Matches in KATKA Kernels and Minimizer Digests

Authors: Dominika Draesslerová, Omar Ahmed, Travis Gagie, Jan Holub, Ben Langmead, Giovanni Manzini, and Gonzalo Navarro

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

Abstract
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.
Cite as

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}
}
Document
DOI: 10.4230/LIPIcs.SEA.2024.14
Accelerating ILP Solvers for Minimum Flow Decompositions Through Search Space and Dimensionality Reductions

Authors: Andreas Grigorjew, Fernando H. C. Dias, Andrea Cracco, Romeo Rizzi, and Alexandru I. Tomescu

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

Abstract
Given a flow network, the Minimum Flow Decomposition (MFD) problem is finding the smallest possible set of weighted paths whose superposition equals the flow. It is a classical, strongly NP-hard problem that is proven to be useful in RNA transcript assembly and applications outside of Bioinformatics. We improve an existing ILP (Integer Linear Programming) model by Dias et al. [RECOMB 2022] for DAGs by decreasing the solver’s search space using solution safety and several other optimizations. This results in a significant speedup compared to the original ILP, of up to 34× on average on the hardest instances. Moreover, we show that our optimizations apply also to MFD problem variants, resulting in speedups that go up to 219× on the hardest instances. We also developed an ILP model of reduced dimensionality for an MFD variant in which the solution path weights are restricted to a given set. This model can find an optimal MFD solution for most instances, and overall, its accuracy significantly outperforms that of previous greedy algorithms while being up to an order of magnitude faster than our optimized ILP.
Cite as

Andreas Grigorjew, Fernando H. C. Dias, Andrea Cracco, Romeo Rizzi, and Alexandru I. Tomescu. Accelerating ILP Solvers for Minimum Flow Decompositions Through Search Space and Dimensionality Reductions. In 22nd International Symposium on Experimental Algorithms (SEA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 301, pp. 14:1-14:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{grigorjew_et_al:LIPIcs.SEA.2024.14,
  author =	{Grigorjew, Andreas and Dias, Fernando H. C. and Cracco, Andrea and Rizzi, Romeo and Tomescu, Alexandru I.},
  title =	{{Accelerating ILP Solvers for Minimum Flow Decompositions Through Search Space and Dimensionality Reductions}},
  booktitle =	{22nd International Symposium on Experimental Algorithms (SEA 2024)},
  pages =	{14:1--14:19},
  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.2024.14},
  URN =		{urn:nbn:de:0030-drops-203792},
  doi =		{10.4230/LIPIcs.SEA.2024.14},
  annote =	{Keywords: Flow decomposition, Integer Linear Programming, Safety, RNA-seq, RNA transcript assembly, isoform}
}
Document
DOI: 10.4230/LIPIcs.SEA.2024.21
SPIDER: Improved Succinct Rank and Select Performance

Authors: Matthew D. Laws, Jocelyn Bliven, Kit Conklin, Elyes Laalai, Samuel McCauley, and Zach S. Sturdevant

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

Abstract
Rank and select data structures seek to preprocess a bit vector to quickly answer two kinds of queries: Rank(i) gives the number of 1 bits in slots 0 through i, and Select(j) gives the first slot s with Rank(s) = j. A succinct data structure can answer these queries while using space much smaller than the size of the original bit vector. State of the art succinct rank and select data structures use as little as 4% extra space (over the underlying bit vector) while answering rank and select queries very quickly. Rank queries can be answered using only a handful of array accesses. Select queries can be answered by starting with similar array accesses, followed by a linear scan through the bit vector. Nonetheless, a tradeoff remains: data structures that use under 4% space are significantly slower at answering rank and select queries than less-space-efficient data structures (using, say, over 20% extra space). In this paper we make significantly progress towards closing this gap. We give a new data structure, SPIDER, which uses 3.82% extra space. SPIDER gives the best known rank query time for data sets of 8 billion or more bits, even compared to much less space-efficient data structures. For select queries, SPIDER outperforms all data structures that use less than 4% space, and significantly closes the gap in select performance between data structures with less than 4% space, and those that use more (over 20% for both rank and select) space. SPIDER makes two main technical contributions. For rank queries, it improves performance by interleaving the metadata with the bit vector to improve cache efficiency. For select queries, it uses predictions to almost eliminate the cost of the linear scan. These predictions are inspired by recent results on data structures with machine-learned predictions, adapted to the succinct data structure setting. Our results hold on both real and synthetic data, showing that these predictions are effective in practice.
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Matthew D. Laws, Jocelyn Bliven, Kit Conklin, Elyes Laalai, Samuel McCauley, and Zach S. Sturdevant. SPIDER: Improved Succinct Rank and Select Performance. In 22nd International Symposium on Experimental Algorithms (SEA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 301, pp. 21:1-21:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{laws_et_al:LIPIcs.SEA.2024.21,
  author =	{Laws, Matthew D. and Bliven, Jocelyn and Conklin, Kit and Laalai, Elyes and McCauley, Samuel and Sturdevant, Zach S.},
  title =	{{SPIDER: Improved Succinct Rank and Select Performance}},
  booktitle =	{22nd International Symposium on Experimental Algorithms (SEA 2024)},
  pages =	{21:1--21:18},
  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.2024.21},
  URN =		{urn:nbn:de:0030-drops-203865},
  doi =		{10.4230/LIPIcs.SEA.2024.21},
  annote =	{Keywords: Rank and Select, Succinct Data Structures, Data Structres, Cache Performance, Predictions}
}
Document
DOI: 10.4230/LIPIcs.SEA.2024.24
Efficient Exact Online String Matching Through Linked Weak Factors

Authors: Matthew N. Palmer, Simone Faro, and Stefano Scafiti

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

Abstract
Online exact string matching is a fundamental computational problem in computer science, involving the sequential search for a pattern within a large text without prior access to the entire text. Its significance is underscored by its diverse applications in data compression, data mining, text editing, and bioinformatics, just to cite a few, where efficient substring matching is crucial. While the problem has been a subject of study for years, recent decades have witnessed a heightened focus on experimental solutions, employing various techniques to achieve superior performance. Notably, approaches centered around weak factor recognition have emerged as leaders in experimental settings, gaining increasing attention. This paper introduces Hash Chain, a novel algorithm founded on a robust weak factor recognition approach that links adjacent factors through hashing. Building upon the efficacy of weak recognition techniques, the proposed algorithm incorporates innovative strategies for organizing data structures and optimizations to enhance performance. Despite its quadratic worst-case time complexity, the new proposed algorithm demonstrates sublinear behavior in practice, outperforming currently known algorithms in the literature.
Cite as

Matthew N. Palmer, Simone Faro, and Stefano Scafiti. Efficient Exact Online String Matching Through Linked Weak Factors. In 22nd International Symposium on Experimental Algorithms (SEA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 301, pp. 24:1-24:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{palmer_et_al:LIPIcs.SEA.2024.24,
  author =	{Palmer, Matthew N. and Faro, Simone and Scafiti, Stefano},
  title =	{{Efficient Exact Online String Matching Through Linked Weak Factors}},
  booktitle =	{22nd International Symposium on Experimental Algorithms (SEA 2024)},
  pages =	{24:1--24:14},
  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.2024.24},
  URN =		{urn:nbn:de:0030-drops-203896},
  doi =		{10.4230/LIPIcs.SEA.2024.24},
  annote =	{Keywords: String matching, text processing, weak recognition, hashing, experimental algorithms, design and analysis of algorithms}
}
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