26 Search Results for "Ouangraoua, A�da"

Document
Complete Volume
DOI: 10.4230/LIPIcs.WABI.2023
LIPIcs, Volume 273, WABI 2023, Complete Volume

Authors: Djamal Belazzougui and Aïda Ouangraoua

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
LIPIcs, Volume 273, WABI 2023, Complete Volume
Cite as

23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 1-400, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Proceedings{belazzougui_et_al:LIPIcs.WABI.2023,
  title =	{{LIPIcs, Volume 273, WABI 2023, Complete Volume}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{1--400},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023},
  URN =		{urn:nbn:de:0030-drops-186250},
  doi =		{10.4230/LIPIcs.WABI.2023},
  annote =	{Keywords: LIPIcs, Volume 273, WABI 2023, Complete Volume}
}
Document
Front Matter
DOI: 10.4230/LIPIcs.WABI.2023.0
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Djamal Belazzougui and Aïda Ouangraoua

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
Front Matter, Table of Contents, Preface, Conference Organization
Cite as

23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 0:i-0:xiv, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{belazzougui_et_al:LIPIcs.WABI.2023.0,
  author =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{0:i--0:xiv},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.0},
  URN =		{urn:nbn:de:0030-drops-186267},
  doi =		{10.4230/LIPIcs.WABI.2023.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Invited Talk
DOI: 10.4230/LIPIcs.WABI.2023.1
Algorithmic Approaches to Study Mutational Processes in Cancer (Invited Talk)

Authors: Teresa M. Przytycka

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
Mutations are the driving force of evolution, yet they underlie many diseases and, in particular, cancer. They are thought to arise from a combination of stochastic errors in DNA processing, naturally occurring DNA damage (e.g., the spontaneous deamination of methylated CpG sites), replication errors, carcinogenic exposures or cancer related aberrations of DNA maintenance machinery. These processes often lead to distinctive patterns of mutations, called "mutational signatures". Starting with the seminal work of Alexandrov at al. [Ludmil B Alexandrov et al., 2013] several computational approaches have been developed to uncover such mutational signatures. However connecting mutational signatures to mutational processes is not always easy [Kim et al., 2021]. To gain insights into the relationships between mutational processes and computationally derived somatic mutation patterns (mutational signatures), we developed several complementary approaches that leverage different algorithmic techniques allowing us to link such patterns to their potential causes. For example, to investigate the genetic aberrations associated with mutational signatures, we took a network-based approach considering mutational signatures as phenotypes. Specifically, our analysis aims to answer the following two complementary questions: (i) what are functional pathways whose gene expression activities correlate with the strengths of mutational signatures, and (ii) are there pathways whose genetic alterations might have led to specific mutational signatures? To identify mutated pathways, we adopted an optimization method based on integer linear programming. Analyzing a breast cancer dataset, we identified pathways associated with mutational signatures on both expression and mutation levels. Our analysis captured important differences in the etiology of the APOBEC related signatures and the two clock-like signatures. In particular, it revealed that clustered and dispersed APOBEC mutations may be caused by different mutagenic processes. In addition, our analysis elucidated differences between two age related signatures - one of the signatures is correlated with the expression of cell cycle genes while the other has no such correlation but shows patterns consistent with the exposure to environmental/external processes [Kim et al., 2020]. Complementing this approach, we also developed a network-based method, named GENESIGNET that constructs an influence/information flow network connecting genes and mutational signatures [Amgalan et al., 2023]. The approach leverages sparse partial correlation among other statistical techniques to uncover dominant influence relations between the activities of network nodes. Applying GENESIGNET to cancer data sets, we uncovered important relations between mutational signatures and several cellular processes that can shed light on cancer-related processes. In particular, GENESIGNET exposed a link between the SBS8 signature of unknown etiology and the Nucleotide Excision Repair (NER) pathway. Linking mutational signatures to molecular features can help understand the etiology and develop personalized cancer therapy. However, due to the complex and dynamic nature of tumor evolution, untangling the cause and effect relationship can be challenging and requires further integrated and comprehensive analyses.
Cite as

Teresa M. Przytycka. Algorithmic Approaches to Study Mutational Processes in Cancer (Invited Talk). In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 1:1-1:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{przytycka:LIPIcs.WABI.2023.1,
  author =	{Przytycka, Teresa M.},
  title =	{{Algorithmic Approaches to Study Mutational Processes in Cancer}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{1:1--1:2},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.1},
  URN =		{urn:nbn:de:0030-drops-186278},
  doi =		{10.4230/LIPIcs.WABI.2023.1},
  annote =	{Keywords: Biological Networks, Cancer, Mutational Signatures, DNA Damage, DNA Repair}
}
Document
Abstract
DOI: 10.4230/LIPIcs.WABI.2023.2
EMMA: Adding Sequences into a Constraint Alignment with High Accuracy and Scalability (Abstract)

Authors: Chengze Shen, Baqiao Liu, Kelly P. Williams, and Tandy Warnow

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
Multiple sequence alignment (MSA) is a crucial precursor to many downstream biological analyses, such as phylogeny estimation [Morrison, 2006], RNA structure prediction [Shapiro et al., 2007], protein structure prediction [Jumper et al., 2021], etc. Obtaining an accurate MSA can be challenging, especially when the dataset is large (i.e., more than 1000 sequences). A key technique for large-scale MSA estimation is to add sequences into an existing alignment. For example, biological knowledge can be used to form a reference alignment on a subset of the sequences, and then the remaining sequences can be added to the reference alignment. Another case where adding sequences into an existing alignment occurs is when new sequences or genomes are added to databases, leading to the opportunity to add the new sequences for each gene in the genome into a growing alignment. A third case is for de novo multiple sequence alignment, where a subset of the sequences is selected and aligned, and then the remaining sequences are added into this "backbone alignment" [Nguyen et al., 2015; Park et al., 2023; Shen et al., 2022; Liu and Warnow, 2023; Park and Warnow, 2023; Yamada et al., 2016]. Thus, adding sequences into existing alignments is a natural problem with multiple applications to biological sequence analysis. A few methods have been developed to add sequences into an existing alignment, with MAFFT--add [Katoh and Frith, 2012] perhaps the most well-known. However, several multiple sequence alignment methods that operate in two steps (first extract and align the backbone sequences and then add the remaining sequences into this backbone alignment) also provide utilities for adding sequences into a user-provided alignment. We present EMMA, a new approach for adding "query" sequences into an existing "constraint" alignment. By construction, EMMA never changes the constraint alignment, except through the introduction of additional sites to represent homologies between the query sequences. EMMA uses a divide-and-conquer technique combined with MAFFT--add (using the most accurate setting, MAFFT-linsi--add) to add sequences into a user-provided alignment. We evaluate EMMA by comparing it to MAFFT-linsi--add, MAFFT--add (the default setting), and WITCH-ng-add. We include a range of biological and simulated datasets (nucleotides and proteins) ranging in size from 1000 to almost 200,000 sequences and evaluate alignment accuracy and scalability. MAFFT-linsi--add was the slowest and least scalable method, only able to run on datasets with at most 1000 sequences in this study, but had excellent accuracy (often the best) on those datasets. We also see that EMMA has better recall than WITCH-ng-add and MAFFT--add on large datasets, especially when the backbone alignment is small or clade-based.
Cite as

Chengze Shen, Baqiao Liu, Kelly P. Williams, and Tandy Warnow. EMMA: Adding Sequences into a Constraint Alignment with High Accuracy and Scalability (Abstract). In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 2:1-2:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{shen_et_al:LIPIcs.WABI.2023.2,
  author =	{Shen, Chengze and Liu, Baqiao and Williams, Kelly P. and Warnow, Tandy},
  title =	{{EMMA: Adding Sequences into a Constraint Alignment with High Accuracy and Scalability}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{2:1--2:2},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.2},
  URN =		{urn:nbn:de:0030-drops-186285},
  doi =		{10.4230/LIPIcs.WABI.2023.2},
  annote =	{Keywords: Multiple sequence alignment, constraint alignment, MAFFT}
}
Document
Abstract
DOI: 10.4230/LIPIcs.WABI.2023.3
BATCH-SCAMPP: Scaling Phylogenetic Placement Methods to Place Many Sequences (Abstract)

Authors: Eleanor Wedell, Chengze Shen, and Tandy Warnow

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
Phylogenetic placement is the problem of placing one or more query sequences into a phylogenetic "backbone" tree, which may be a maximum likelihood tree on a multiple sequence alignment for a single gene, a taxonomy with leaves labeled by sequences for a single gene [Nidhi Shah et al., 2021], or a species tree [Jiang et al., 2023]. When the backbone tree is a tree estimated on a single gene, the most accurate techniques for phylogenetic placement are likelihood-based, and can be computationally intensive when the backbone trees are large [Chu and Warnow, 2023]. Phylogenetic placement into gene trees occurs when updating existing gene trees with newly observed sequences, but can also be applied in the "bulk" context, where many sequences are placed at the same time into the backbone tree. For example, phylogenetic placement can be used to taxonomically characterize shotgun sequencing reads generated for an environmental sample in metagenomic analysis [Nidhi Shah et al., 2021; Barbera et al., 2019]. The two most well known maximum likelihood phylogenetic placement methods are pplacer [Chu and Warnow, 2023] and EPA-ng [Barbera et al., 2019]. Of these two, EPA-ng is optimized for scaling the number of query sequences and is capable of placing millions of sequences into phylogenetic trees of up to a few thousand sequences [Barbera et al., 2019], and achieves sublinear runtime in the number of query sequences (see Figure 2 from [Balaban et al., 2022]). Previously we introduced the SCAMPP framework [Wedell et al., 2022] to enable both pplacer and EPA-ng to perform phylogenetic placement into ultra-large backbone trees, and we demonstrated its utility for placing into backbone trees with up to 200,000 sequences. By using maximum likelihood methods pplacer or EPA-ng within the SCAMPP framework, the resulting placements are more accurate than with APPLES-2 [Balaban et al., 2022], with the most notable accuracy improvement for fragmentary sequences, and are computationally similar for single query sequence placement [Wedell et al., 2022]. However, SCAMPP was designed to incrementally update a large tree, one query sequence at a time, and was not optimized for the other uses of phylogenetic placement, where batch placement of many sequencing reads is required. Here we introduce BATCH-SCAMPP, a technique that improves scalability in both dimensions: the number of query sequences being placed into the backbone tree and the size of the backbone tree. Furthermore, BATCH-SCAMPP is specifically designed to improve EPA-ng’s scalability to large backbone trees. Although BATCH-SCAMPP is based on SCAMPP, it uses a substantially modified design in order to be able to take advantage of EPA-ng’s ability to place many query sequences efficiently. The BATCH-SCAMPP method operates by allowing the input set of query sequences to suggest and then vote on placement subtrees, thus enabling many query sequences to select the same placement subtree. We pair BATCH-SCAMPP with EPA-ng to explore the capability of this approach for scaling to many query sequences. We show that this combination of techniques (which we call BSCAMPP+EPA-ng, or BSCAMPP(e)) not only provides high accuracy and scalability to large backbone trees, matching that of SCAMPP used with EPA-ng (i.e., SCAMPP(e)), but also achieves the goal of scaling sublinearly in the number of query sequences. Moreover, it is much more scalable than EPA-ng and faster than SCAMPP+EPA-ng: when placing 10,000 sequences into a backbone tree of 50,000 leaves, EPA-ng is unable to run due to memory issues, SCAMPP+EPA-ng requires 1421 minutes, and BSCAMPP(e) places all sequences in 7 minutes (all given the same computational resources. Figure 1 gives an example of this performance advantage on the nt78 [Chu and Warnow, 2023] simulated dataset.
Cite as

Eleanor Wedell, Chengze Shen, and Tandy Warnow. BATCH-SCAMPP: Scaling Phylogenetic Placement Methods to Place Many Sequences (Abstract). In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 3:1-3:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{wedell_et_al:LIPIcs.WABI.2023.3,
  author =	{Wedell, Eleanor and Shen, Chengze and Warnow, Tandy},
  title =	{{BATCH-SCAMPP: Scaling Phylogenetic Placement Methods to Place Many Sequences}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{3:1--3:2},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.3},
  URN =		{urn:nbn:de:0030-drops-186296},
  doi =		{10.4230/LIPIcs.WABI.2023.3},
  annote =	{Keywords: Phylogenetic Placement, EPA-ng, Phylogenetics}
}
Document
DOI: 10.4230/LIPIcs.WABI.2023.4
Optimal Subtree Prune and Regraft for Quartet Score in Sub-Quadratic Time

Authors: Shayesteh Arasti and Siavash Mirarab

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
Finding a tree with the minimum total distance to a given set of trees (the median tree) is increasingly needed in phylogenetics. Defining tree distance as the number of induced four-taxon unrooted (i.e., quartet) trees with different topologies, the median of a set of gene trees is a statistically consistent estimator of the species tree under several models of gene tree species tree discordance. Because of this, median trees defined with quartet distance are widely used in practice for species tree inference. Nevertheless, the problem is NP-Hard and the widely-used solutions are heuristics. In this paper, we pave the way for a new type of heuristic solution to this problem. We show that the optimal place to add a subtree of size m onto a tree with n leaves can be found in time that grows quasi-linearly with n and is nearly independent of m. This algorithm can be used to perform subtree prune and regraft (SPR) moves efficiently, which in turn enables the hill-climbing heuristic search for the optimal tree. In exploratory experiments, we show that our algorithm can improve the quartet score of trees obtained using the existing widely-used methods.
Cite as

Shayesteh Arasti and Siavash Mirarab. Optimal Subtree Prune and Regraft for Quartet Score in Sub-Quadratic Time. In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 4:1-4:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{arasti_et_al:LIPIcs.WABI.2023.4,
  author =	{Arasti, Shayesteh and Mirarab, Siavash},
  title =	{{Optimal Subtree Prune and Regraft for Quartet Score in Sub-Quadratic Time}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{4:1--4:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.4},
  URN =		{urn:nbn:de:0030-drops-186309},
  doi =		{10.4230/LIPIcs.WABI.2023.4},
  annote =	{Keywords: Phylogenetics, Gene tree discordance, Quartet score, Quartet distance, Subtree prune and regraft, Tree search, ASTRAL}
}
Document
DOI: 10.4230/LIPIcs.WABI.2023.5
Leveraging Constraints Plus Dynamic Programming for the Large Dollo Parsimony Problem

Authors: Junyan Dai, Tobias Rubel, Yunheng Han, and Erin K. Molloy

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
The last decade of phylogenetics has seen the development of many methods that leverage constraints plus dynamic programming. The goal of this algorithmic technique is to produce a phylogeny that is optimal with respect to some objective function and that lies within a constrained version of tree space. The popular species tree estimation method ASTRAL, for example, returns a tree that (1) maximizes the quartet score computed with respect to the input gene trees and that (2) draws its branches (bipartitions) from the input constraint set. This technique has yet to be used for classic parsimony problems where the input are binary characters, sometimes with missing values. Here, we introduce the clade-constrained character parsimony problem and present an algorithm that solves this problem in polynomial time for the Dollo criterion score. Dollo parsimony, which requires traits/mutations to be gained at most once but allows them to be lost any number of times, is widely used for tumor phylogenetics as well as species phylogenetics, for example analyses of low-homoplasy retroelement insertions across the vertebrate tree of life. Thus, we implement our algorithm in a software package, called Dollo-CDP, and evaluate its utility in the context of species phylogenetics using both simulated and real data sets. Our results show that Dollo-CDP can improve upon heuristic search from a single starting tree, often recovering a better scoring tree. Moreover, Dollo-CDP scales to data sets with much larger numbers of taxa than branch-and-bound while still having an optimality guarantee, albeit a more restricted one. Lastly, we show that our algorithm for Dollo parsimony can easily be adapted to Camin-Sokal parsimony but not Fitch parsimony.
Cite as

Junyan Dai, Tobias Rubel, Yunheng Han, and Erin K. Molloy. Leveraging Constraints Plus Dynamic Programming for the Large Dollo Parsimony Problem. In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 5:1-5:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{dai_et_al:LIPIcs.WABI.2023.5,
  author =	{Dai, Junyan and Rubel, Tobias and Han, Yunheng and Molloy, Erin K.},
  title =	{{Leveraging Constraints Plus Dynamic Programming for the Large Dollo Parsimony Problem}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{5:1--5:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.5},
  URN =		{urn:nbn:de:0030-drops-186312},
  doi =		{10.4230/LIPIcs.WABI.2023.5},
  annote =	{Keywords: phylogenetics, parsimony, Dollo, Camin-Sokal, dynamic programming, constraints}
}
Document
DOI: 10.4230/LIPIcs.WABI.2023.6
Simultaneous Reconstruction of Duplication Episodes and Gene-Species Mappings

Authors: Paweł Górecki, Natalia Rutecka, Agnieszka Mykowiecka, and Jarosław Paszek

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
We present a novel problem, called MetaEC, which aims to infer gene-species assignments in a collection of gene trees with missing labels by minimizing the size of duplication episode clustering (EC). This problem is particularly relevant in metagenomics, where incomplete data often poses a challenge in the accurate reconstruction of gene histories. To solve MetaEC, we propose a polynomial time dynamic programming (DP) formulation that verifies the existence of a set of duplication episodes from a predefined set of episode candidates. We then demonstrate how to use DP to design an algorithm that solves MetaEC. Although the algorithm is exponential in the worst case, we introduce a heuristic modification of the algorithm that provides a solution with the knowledge that it is exact. To evaluate our method, we perform two computational experiments on simulated and empirical data containing whole genome duplication events, showing that our algorithm is able to accurately infer the corresponding events.
Cite as

Paweł Górecki, Natalia Rutecka, Agnieszka Mykowiecka, and Jarosław Paszek. Simultaneous Reconstruction of Duplication Episodes and Gene-Species Mappings. In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 6:1-6:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{gorecki_et_al:LIPIcs.WABI.2023.6,
  author =	{G\'{o}recki, Pawe{\l} and Rutecka, Natalia and Mykowiecka, Agnieszka and Paszek, Jaros{\l}aw},
  title =	{{Simultaneous Reconstruction of Duplication Episodes and Gene-Species Mappings}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{6:1--6:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.6},
  URN =		{urn:nbn:de:0030-drops-186329},
  doi =		{10.4230/LIPIcs.WABI.2023.6},
  annote =	{Keywords: Genomic Duplication, Gene-Species Mapping, Duplication Episode, Gene Tree, Species Tree}
}
Document
DOI: 10.4230/LIPIcs.WABI.2023.7
Making a Network Orchard by Adding Leaves

Authors: Leo van Iersel, Mark Jones, Esther Julien, and Yukihiro Murakami

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
Phylogenetic networks are used to represent the evolutionary history of species. Recently, the new class of orchard networks was introduced, which were later shown to be interpretable as trees with additional horizontal arcs. This makes the network class ideal for capturing evolutionary histories that involve horizontal gene transfers. Here, we study the minimum number of additional leaves needed to make a network orchard. We demonstrate that computing this proximity measure for a given network is NP-hard and describe a tight upper bound. We also give an equivalent measure based on vertex labellings to construct a mixed integer linear programming formulation. Our experimental results, which include both real-world and synthetic data, illustrate the efficiency of our implementation.
Cite as

Leo van Iersel, Mark Jones, Esther Julien, and Yukihiro Murakami. Making a Network Orchard by Adding Leaves. In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 7:1-7:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{vaniersel_et_al:LIPIcs.WABI.2023.7,
  author =	{van Iersel, Leo and Jones, Mark and Julien, Esther and Murakami, Yukihiro},
  title =	{{Making a Network Orchard by Adding Leaves}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{7:1--7:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.7},
  URN =		{urn:nbn:de:0030-drops-186333},
  doi =		{10.4230/LIPIcs.WABI.2023.7},
  annote =	{Keywords: Phylogenetics, Network, Orchard Networks, Proximity Measures, NP-hardness}
}
Document
Abstract
DOI: 10.4230/LIPIcs.WABI.2023.8
Quartets Enable Statistically Consistent Estimation of Cell Lineage Trees Under an Unbiased Error and Missingness Model (Abstract)

Authors: Yunheng Han and Erin K. Molloy

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
Cancer progression and treatment can be informed by reconstructing its evolutionary history from tumor cells [Lim et al., 2020]. Although many methods exist to estimate evolutionary trees (called phylogenies) from molecular sequences, traditional approaches assume the input data are error-free and the output tree is fully resolved. These assumptions are challenged in tumor phylogenetics because single-cell sequencing produces sparse, error-ridden data and because tumors evolve clonally [Jahn et al., 2016; Schwartz and Schäffer, 2017]. Here, we study the theoretical utility of methods based on quartets (four-leaf, unrooted phylogenetic trees) and triplets (three-leaf, rooted phylogenetic trees), in light of these barriers. Quartets and triplets have long been used as the building blocks for reconstructing the evolutionary history of species [Wilkinson et al., 2005]. The reason triplet-based methods (e.g., MP-EST [Liu et al., 2010]) and quartet-based methods (e.g., ASTRAL [Mirarab et al., 2014]) have garnered such success in species phylogenetics is their good statistical properties under the Multi-Species Coalescent (MSC) model [Pamilo and Nei, 1988; Rannala and Yang, 2003]; see Allman et al. (2011) and Degnan (2006) for identifiability results under the MSC model for quartets and triplets, respectively. Inspired by these efforts, we study the utility of quartets and triplets for estimating cell lineage trees under a popular tumor phylogenetics model [Jahn et al., 2016; Ross and Markowetz, 2016; Wu, 2019; Kizilkale et al., 2022] with two phases. First, mutations arise on a (highly unresolved) cell lineage tree according to the infinite sites model, and second, errors (false positives and false negatives) and missing values are introduced to the resulting mutation data in an unbiased fashion, mimicking data produced by single-cell sequencing protocols. This infinite sites plus unbiased error and missingness (IS+UEM) model generates mutations (rather than gene genealogies like the MSC model). However, a quartet (with leaves bijectively labeled by four cells) is implied by a mutation being present in two cells and absent from two cells [Molloy et al., 2021; Springer et al., 2019]; similarly, a triplet (on three cells) is implied by a mutation being present in two cells and absent from one cell. Our main result is that under the IS+UEM, the most probable quartet identifies the unrooted model cell lineage tree on four cells, with a mild assumption: the probability of false negatives and the probability of false positives must not sum to one. Somewhat surprisingly, our identifiability result for quartets does not extend to triplets, with more restrictive assumptions being required for identifiability. These results motivate seeking an unrooted cell lineage tree such that the number of quartets shared between it and the input mutations is maximized. We prove an optimal solution to this problem is a consistent estimator of the unrooted cell lineage tree under the IS+UEM model; this guarantee includes the case where the model tree is highly unresolved, provided that tree error is defined as the number of false negative branches. We therefore conclude by outlining how quartet-based methods might be employed for tumor phylogenetics given other important challenges like copy number aberrations and doublets.
Cite as

Yunheng Han and Erin K. Molloy. Quartets Enable Statistically Consistent Estimation of Cell Lineage Trees Under an Unbiased Error and Missingness Model (Abstract). In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 8:1-8:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{han_et_al:LIPIcs.WABI.2023.8,
  author =	{Han, Yunheng and Molloy, Erin K.},
  title =	{{Quartets Enable Statistically Consistent Estimation of Cell Lineage Trees Under an Unbiased Error and Missingness Model}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{8:1--8:2},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.8},
  URN =		{urn:nbn:de:0030-drops-186347},
  doi =		{10.4230/LIPIcs.WABI.2023.8},
  annote =	{Keywords: Tumor Phylogenetics, Cell Lineage Trees, Quartets, Supertrees, ASTRAL}
}
Document
DOI: 10.4230/LIPIcs.WABI.2023.9
Inferring Temporally Consistent Migration Histories

Authors: Mrinmoy Saha Roddur, Sagi Snir, and Mohammed El-Kebir

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
Not only do many biological populations undergo evolution, but population members may also migrate from one location to another. For example, tumor cells may migrate from the primary tumor and seed a new metastasis, and pathogens may migrate from one host to another. One may represent a population’s migration history by labeling the vertices of a given phylogeny T with locations such that an edge incident to vertices with distinct locations represents a migration. Additionally, in some biological populations, taxa from distinct lineages may comigrate from one location to another in a single event, a phenomenon known as a comigration. Here, we show that a previous problem statement for inferring migration histories that are parsimonious in terms of migrations and comigrations may lead to temporally inconsistent solutions. To remedy this deficiency, we introduce precise definitions of temporal consistency of comigrations in a phylogeny, leading to three successive problems. First, we formulate the Temporally Consistent Comigrations (TCC) problem to check if a set of comigrations is temporally consistent and provide a linear time algorithm for solving this problem. Second, we formulate the Parsimonious Consistent Comigration (PCC) problem, which aims to find comigrations given a location labeling of a phylogeny. We show that PCC is NP-hard. Third, we formulate the Parsimonious Consistent Comigration History (PCCH) problem, which infers the migration history given a phylogeny and locations of its extant vertices only. We show that PCCH is NP-hard as well. On the positive side, we propose integer linear programming models to solve the PCC and PCCH problems. We apply our approach to real and simulated data.
Cite as

Mrinmoy Saha Roddur, Sagi Snir, and Mohammed El-Kebir. Inferring Temporally Consistent Migration Histories. In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 9:1-9:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{roddur_et_al:LIPIcs.WABI.2023.9,
  author =	{Roddur, Mrinmoy Saha and Snir, Sagi and El-Kebir, Mohammed},
  title =	{{Inferring Temporally Consistent Migration Histories}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{9:1--9:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.9},
  URN =		{urn:nbn:de:0030-drops-186357},
  doi =		{10.4230/LIPIcs.WABI.2023.9},
  annote =	{Keywords: Metastasis, Migration, Integer Linear Programming, Maximum parsimony}
}
Document
DOI: 10.4230/LIPIcs.WABI.2023.10
Finding Maximal Exact Matches in Graphs

Authors: Nicola Rizzo, Manuel Cáceres, and Veli Mäkinen

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
We study the problem of finding maximal exact matches (MEMs) between a query string Q and a labeled graph G. MEMs are an important class of seeds, often used in seed-chain-extend type of practical alignment methods because of their strong connections to classical metrics. A principled way to speed up chaining is to limit the number of MEMs by considering only MEMs of length at least κ (κ-MEMs). However, on arbitrary input graphs, the problem of finding MEMs cannot be solved in truly sub-quadratic time under SETH (Equi et al., ICALP 2019) even on acyclic graphs. In this paper we show an O(n⋅ L ⋅ d^{L-1} + m + M_{κ,L})-time algorithm finding all κ-MEMs between Q and G spanning exactly L nodes in G, where n is the total length of node labels, d is the maximum degree of a node in G, m = |Q|, and M_{κ,L} is the number of output MEMs. We use this algorithm to develop a κ-MEM finding solution on indexable Elastic Founder Graphs (Equi et al., Algorithmica 2022) running in time O(nH² + m + M_κ), where H is the maximum number of nodes in a block, and M_κ is the total number of κ-MEMs. Our results generalize to the analysis of multiple query strings (MEMs between G and any of the strings). Additionally, we provide some preliminary experimental results showing that the number of graph MEMs is an order of magnitude smaller than the number of string MEMs of the corresponding concatenated collection.
Cite as

Nicola Rizzo, Manuel Cáceres, and Veli Mäkinen. Finding Maximal Exact Matches in Graphs. In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 10:1-10:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{rizzo_et_al:LIPIcs.WABI.2023.10,
  author =	{Rizzo, Nicola and C\'{a}ceres, Manuel and M\"{a}kinen, Veli},
  title =	{{Finding Maximal Exact Matches in Graphs}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{10:1--10:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.10},
  URN =		{urn:nbn:de:0030-drops-186364},
  doi =		{10.4230/LIPIcs.WABI.2023.10},
  annote =	{Keywords: Sequence to graph alignment, bidirectional BWT, r-index, suffix tree, founder graphs}
}
Document
DOI: 10.4230/LIPIcs.WABI.2023.11
Revisiting the Complexity of and Algorithms for the Graph Traversal Edit Distance and Its Variants

Authors: Yutong Qiu, Yihang Shen, and Carl Kingsford

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
The graph traversal edit distance (GTED), introduced by Ebrahimpour Boroojeny et al. (2018), is an elegant distance measure defined as the minimum edit distance between strings reconstructed from Eulerian trails in two edge-labeled graphs. GTED can be used to infer evolutionary relationships between species by comparing de Bruijn graphs directly without the computationally costly and error-prone process of genome assembly. Ebrahimpour Boroojeny et al. (2018) propose two ILP formulations for GTED and claim that GTED is polynomially solvable because the linear programming relaxation of one of the ILPs will always yield optimal integer solutions. The claim that GTED is polynomially solvable is contradictory to the complexity of existing string-to-graph matching problems. We resolve this conflict in complexity results by proving that GTED is NP-complete and showing that the ILPs proposed by Ebrahimpour Boroojeny et al. do not solve GTED but instead solve for a lower bound of GTED and are not solvable in polynomial time. In addition, we provide the first two, correct ILP formulations of GTED and evaluate their empirical efficiency. These results provide solid algorithmic foundations for comparing genome graphs and point to the direction of heuristics that estimate GTED efficiently.
Cite as

Yutong Qiu, Yihang Shen, and Carl Kingsford. Revisiting the Complexity of and Algorithms for the Graph Traversal Edit Distance and Its Variants. In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 11:1-11:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{qiu_et_al:LIPIcs.WABI.2023.11,
  author =	{Qiu, Yutong and Shen, Yihang and Kingsford, Carl},
  title =	{{Revisiting the Complexity of and Algorithms for the Graph Traversal Edit Distance and Its Variants}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{11:1--11:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.11},
  URN =		{urn:nbn:de:0030-drops-186374},
  doi =		{10.4230/LIPIcs.WABI.2023.11},
  annote =	{Keywords: Integer Linear Programming, Genome Graphs, Flow Network, Graph Comparison}
}
Document
DOI: 10.4230/LIPIcs.WABI.2023.12
Co-Linear Chaining on Pangenome Graphs

Authors: Jyotshna Rajput, Ghanshyam Chandra, and Chirag Jain

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
Pangenome reference graphs are useful in genomics because they compactly represent the genetic diversity within a species, a capability that linear references lack. However, efficiently aligning sequences to these graphs with complex topology and cycles can be challenging. The seed-chain-extend based alignment algorithms use co-linear chaining as a standard technique to identify a good cluster of exact seed matches that can be combined to form an alignment. Recent works show how the co-linear chaining problem can be efficiently solved for acyclic pangenome graphs by exploiting their small width [Makinen et al., TALG'19] and how incorporating gap cost in the scoring function improves alignment accuracy [Chandra and Jain, RECOMB'23]. However, it remains open on how to effectively generalize these techniques for general pangenome graphs which contain cycles. Here we present the first practical formulation and an exact algorithm for co-linear chaining on cyclic pangenome graphs. We rigorously prove the correctness and computational complexity of the proposed algorithm. We evaluate the empirical performance of our algorithm by aligning simulated long reads from the human genome to a cyclic pangenome graph constructed from 95 publicly available haplotype-resolved human genome assemblies. While the existing heuristic-based algorithms are faster, the proposed algorithm provides a significant advantage in terms of accuracy.
Cite as

Jyotshna Rajput, Ghanshyam Chandra, and Chirag Jain. Co-Linear Chaining on Pangenome Graphs. In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 12:1-12:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{rajput_et_al:LIPIcs.WABI.2023.12,
  author =	{Rajput, Jyotshna and Chandra, Ghanshyam and Jain, Chirag},
  title =	{{Co-Linear Chaining on Pangenome Graphs}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{12:1--12:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.12},
  URN =		{urn:nbn:de:0030-drops-186389},
  doi =		{10.4230/LIPIcs.WABI.2023.12},
  annote =	{Keywords: Sequence alignment, variation graph, genome sequencing, path cover}
}
Document
DOI: 10.4230/LIPIcs.WABI.2023.13
Acceleration of FM-Index Queries Through Prefix-Free Parsing

Authors: Aaron Hong, Marco Oliva, Dominik Köppl, Hideo Bannai, Christina Boucher, and Travis Gagie

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
FM-indexes are a crucial data structure in DNA alignment, but searching with them usually takes at least one random access per character in the query pattern. Ferragina and Fischer [Ferragina and Fischer, 2007] observed in 2007 that word-based indexes often use fewer random accesses than character-based indexes, and thus support faster searches. Since DNA lacks natural word-boundaries, however, it is necessary to parse it somehow before applying word-based FM-indexing. Last year, Deng et al. [Deng et al., 2022] proposed parsing genomic data by induced suffix sorting, and showed the resulting word-based FM-indexes support faster counting queries than standard FM-indexes when patterns are a few thousand characters or longer. In this paper we show that using prefix-free parsing - which takes parameters that let us tune the average length of the phrases - instead of induced suffix sorting, gives a significant speedup for patterns of only a few hundred characters. We implement our method and demonstrate it is between 3 and 18 times faster than competing methods on queries to GRCh38. And was consistently faster on queries made to 25,000, 50,000 and 100,000 SARS-CoV-2 genomes. Hence, it is very clear that our method accelerates the performance of count over all state-of-the-art methods with a minor increase in the memory.
Cite as

Aaron Hong, Marco Oliva, Dominik Köppl, Hideo Bannai, Christina Boucher, and Travis Gagie. Acceleration of FM-Index Queries Through Prefix-Free Parsing. In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 13:1-13:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{hong_et_al:LIPIcs.WABI.2023.13,
  author =	{Hong, Aaron and Oliva, Marco and K\"{o}ppl, Dominik and Bannai, Hideo and Boucher, Christina and Gagie, Travis},
  title =	{{Acceleration of FM-Index Queries Through Prefix-Free Parsing}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{13:1--13:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.13},
  URN =		{urn:nbn:de:0030-drops-186390},
  doi =		{10.4230/LIPIcs.WABI.2023.13},
  annote =	{Keywords: FM-index, pangenomics, scalability, word-based indexing, random access}
}
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