Document

**Published in:** LIPIcs, Volume 265, 21st International Symposium on Experimental Algorithms (SEA 2023)

Given a string X of length n on alphabet σ, the FM-index data structure allows counting all occurrences of a pattern P of length m in O(m) time via an algorithm called backward search. An important difficulty when searching with an FM-index is to support queries on L, the Burrows-Wheeler transform of X, while L is in compressed form. This problem has been the subject of intense research for 25 years now. Run-length encoding of L is an effective way to reduce index size, in particular when the data being indexed is highly-repetitive, which is the case in many types of modern data, including those arising from versioned document collections and in pangenomics. This paper takes a back-to-basics look at supporting backward search in FM-indexes, exploring and engineering two simple designs. The first divides the BWT string into blocks containing b symbols each and then run-length compresses each block separately, possibly introducing new runs (compared to applying run-length encoding once, to the whole string). Each block stores counts of each symbol that occurs before the block. This method supports the operation rank_c(L, i) (i.e., count the number of times c occurs in the prefix L[1..i]) by first determining the block i/b in which i falls and scanning the block to the appropriate position counting occurrences of c along the way. This partial answer to rank_c(L, i) is then added to the stored count of c symbols before the block to determine the final answer. Our second design has a similar structure, but instead divides the run-length-encoded version of L into blocks containing an equal number of runs. The trick then is to determine the block in which a query falls, which is achieved via a predecessor query over the block starting positions. We show via extensive experiments on a wide range of repetitive text collections that these FM-indexes are not only easy to implement, but also fast and space efficient in practice.

Diego Díaz-Domínguez, Saska Dönges, Simon J. Puglisi, and Leena Salmela. Simple Runs-Bounded FM-Index Designs Are Fast. In 21st International Symposium on Experimental Algorithms (SEA 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 265, pp. 7:1-7:16, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)

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@InProceedings{diazdominguez_et_al:LIPIcs.SEA.2023.7, author = {D{\'\i}az-Dom{\'\i}nguez, Diego and D\"{o}nges, Saska and Puglisi, Simon J. and Salmela, Leena}, title = {{Simple Runs-Bounded FM-Index Designs Are Fast}}, booktitle = {21st International Symposium on Experimental Algorithms (SEA 2023)}, pages = {7:1--7:16}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-279-2}, ISSN = {1868-8969}, year = {2023}, volume = {265}, editor = {Georgiadis, Loukas}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2023.7}, URN = {urn:nbn:de:0030-drops-183579}, doi = {10.4230/LIPIcs.SEA.2023.7}, annote = {Keywords: data structures, efficient algorithms} }

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Invited Talk

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

The de Bruijn graph has become a standard method in the analysis of sequencing reads in computational biology due to its ability to represent the information contained in large read sets in small space. A de Bruijn graph represents a set of sequencing reads by its k-mers, i.e. the set of substrings of length k that occur in the reads. In the classical definition, the k-mers are the edges of the graph and the nodes are the k-1 bases long prefixes and suffixes of the k-mers. Usually only k-mers occurring several times in the read set are kept to filter out noise in the data. De Bruijn graphs have been used to solve many problems in computational biology including genome assembly [Ramana M. Idury and Michael S. Waterman, 1995; Pavel A. Pevzner et al., 2001; Anton Bankevich et al., 2012; Yu Peng et al., 2010], sequencing error correction [Leena Salmela and Eric Rivals, 2014; Giles Miclotte et al., 2016; Leena Salmela et al., 2017; Limasset et al., 2019], reference free variant calling [Raluca Uricaru et al., 2015], indexing read sets [Camille Marchet et al., 2021], and so on. Next I will discuss two of these problems in more depth.
The de Bruijn graph first emerged in computation biology in the context of genome assembly [Ramana M. Idury and Michael S. Waterman, 1995; Pavel A. Pevzner et al., 2001] where the task is to reconstruct a genome based on sequencing reads. As the de Bruijn graph can represent large read sets compactly, it became the standard approach to assemble short reads [Anton Bankevich et al., 2012; Yu Peng et al., 2010]. In the theoretical framework of de Bruijn graph based genome assembly, a genome is thought to be the Eulerian path in the de Bruijn graph built on the sequencing reads. In practise, the Eulerian path is not unique and thus not useful in the biological context. Therefore, practical implementations report subpaths that are guaranteed to be part of any Eulerian path and thus part of the actual genome. Such models include unitigs, which are nonbranching paths of the de Bruijn graph, and more involved definitions such as omnitigs [Alexandru I. Tomescu and Paul Medvedev, 2017].
In genome assembly the choice of k is a crucial matter. A small k can result in a tangled graph, whereas a too large k will fragment the graph. Furthermore, a different value of k may be optimal for different parts of the genome. Variable order de Bruijn graphs [Christina Boucher et al., 2015; Djamal Belazzougui et al., 2016], which represent de Bruijn graphs of all orders k in a single data structure, have been proposed as a solution but no rigorous definition corresponding to unitigs has been presented. We give the first definition of assembled sequences, i.e. contigs, on such graphs and an algorithm for enumerating them.
Another problem that can be solved with de Bruijn graphs is the correction of sequencing errors [Leena Salmela and Eric Rivals, 2014; Giles Miclotte et al., 2016; Leena Salmela et al., 2017; Limasset et al., 2019]. Because each position of a genome is sequenced several times, it is possible to correct sequencing errors in reads if we can identify data originating from the same genomic region. A de Bruijn graph can be used to represent compactly the reliable information and the individual reads can be corrected by aligning them to the graph.

Leena Salmela. Efficient Solutions to Biological Problems Using de Bruijn Graphs (Invited Talk). In 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 242, pp. 1:1-1:2, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2022)

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@InProceedings{salmela:LIPIcs.WABI.2022.1, author = {Salmela, Leena}, title = {{Efficient Solutions to Biological Problems Using de Bruijn Graphs}}, booktitle = {22nd International Workshop on Algorithms in Bioinformatics (WABI 2022)}, pages = {1:1--1:2}, 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.2022.1}, URN = {urn:nbn:de:0030-drops-170357}, doi = {10.4230/LIPIcs.WABI.2022.1}, annote = {Keywords: de Bruijn graph, variable order de Bruijn graph, genome assembly, sequencing error correction, k-mers} }

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**Published in:** LIPIcs, Volume 172, 20th International Workshop on Algorithms in Bioinformatics (WABI 2020)

Genome wide optical maps are high resolution restriction maps that give a unique numeric representation to a genome. They are produced by assembling hundreds of thousands of single molecule optical maps, which are called Rmaps. Unfortunately, there exists very few choices for assembling Rmap data. There exists only one publicly-available non-proprietary method for assembly and one proprietary method that is available via an executable. Furthermore, the publicly-available method, by Valouev et al. (2006), follows the overlap-layout-consensus (OLC) paradigm, and therefore, is unable to scale for relatively large genomes. The algorithm behind the proprietary method, Bionano Genomics' Solve, is largely unknown. In this paper, we extend the definition of bi-labels in the paired de Bruijn graph to the context of optical mapping data, and present the first de Bruijn graph based method for Rmap assembly. We implement our approach, which we refer to as rmapper, and compare its performance against the assembler of Valouev et al. (2006) and Solve by Bionano Genomics on data from three genomes - E. coli, human, and climbing perch fish (Anabas Testudineus). Our method was the only one able to successfully run on all three genomes. The method of Valouev et al. (2006) only successfully ran on E. coli and Bionano Solve successfully ran on E. coli and human but not on the fish genome. Moreover, on the human genome rmapper was at least 130 times faster than Bionano Solve, used five times less memory and produced the highest genome fraction with zero mis-assemblies.

Kingshuk Mukherjee, Massimiliano Rossi, Leena Salmela, and Christina Boucher. Fast and Efficient Rmap Assembly Using the Bi-Labelled de Bruijn Graph. In 20th International Workshop on Algorithms in Bioinformatics (WABI 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 172, pp. 9:1-9:16, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2020)

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@InProceedings{mukherjee_et_al:LIPIcs.WABI.2020.9, author = {Mukherjee, Kingshuk and Rossi, Massimiliano and Salmela, Leena and Boucher, Christina}, title = {{Fast and Efficient Rmap Assembly Using the Bi-Labelled de Bruijn Graph}}, booktitle = {20th International Workshop on Algorithms in Bioinformatics (WABI 2020)}, pages = {9:1--9:16}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-161-0}, ISSN = {1868-8969}, year = {2020}, volume = {172}, editor = {Kingsford, Carl and Pisanti, Nadia}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2020.9}, URN = {urn:nbn:de:0030-drops-127982}, doi = {10.4230/LIPIcs.WABI.2020.9}, annote = {Keywords: optical maps, de Bruijn graph, assembly} }

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

Many bioinformatics problems admit a large number of solutions, with no way of distinguishing the correct one among them. One approach of coping with this issue is to look at the partial solutions common to all solutions. Such partial solutions have been called safe, and an algorithm outputting all safe solutions has been called safe and complete. In this paper we develop a general technique that automatically provides a safe and complete algorithm to problems solvable by dynamic programming. We illustrate it by applying it to the bioinformatics problem of RNA folding, assuming the simplistic folding model maximizing the number of paired bases. Our safe and complete algorithm has time complexity O(n^3M(n)) and space complexity O(n^3) where n is the length of the RNA sequence and M(n) in Omega(n) is the time complexity of arithmetic operations on O(n)-bit integers. We also implement this algorithm and show that, despite an exponential number of optimal solutions, our algorithm is efficient in practice.

Niko Kiirala, Leena Salmela, and Alexandru I. Tomescu. Safe and Complete Algorithms for Dynamic Programming Problems, with an Application to RNA Folding. In 30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 128, pp. 8:1-8:16, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2019)

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@InProceedings{kiirala_et_al:LIPIcs.CPM.2019.8, author = {Kiirala, Niko and Salmela, Leena and Tomescu, Alexandru I.}, title = {{Safe and Complete Algorithms for Dynamic Programming Problems, with an Application to RNA Folding}}, booktitle = {30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019)}, pages = {8:1--8:16}, 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.2019.8}, URN = {urn:nbn:de:0030-drops-104794}, doi = {10.4230/LIPIcs.CPM.2019.8}, annote = {Keywords: RNA secondary structure, RNA folding, Safe solution, Safe and complete algorithm, Counting problem} }

Document

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

With long reads getting even longer and cheaper, large scale sequencing projects can be accomplished without short reads at an affordable cost. Due to the high error rates and less mature tools, de novo assembly of long reads is still challenging and often results in a large collection of contigs. Dense linkage maps are collections of markers whose location on the genome is approximately known. Therefore they provide long range information that has the potential to greatly aid in de novo assembly. Previously linkage maps have been used to detect misassemblies and to manually order contigs. However, no fully automated tools exist to incorporate linkage maps in assembly but instead large amounts of manual labour is needed to order the contigs into chromosomes. We formulate the genome assembly problem in the presence of linkage maps and present the first method for guided genome assembly using linkage maps. Our method is based on an additional cleaning step added to the assembly. We show that it can simplify the underlying assembly graph, resulting in more contiguous assemblies and reducing the amount of misassemblies when compared to de novo assembly.

Riku Walve, Pasi Rastas, and Leena Salmela. Kermit: Guided Long Read Assembly using Coloured Overlap Graphs. In 18th International Workshop on Algorithms in Bioinformatics (WABI 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 113, pp. 11:1-11:11, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)

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@InProceedings{walve_et_al:LIPIcs.WABI.2018.11, author = {Walve, Riku and Rastas, Pasi and Salmela, Leena}, title = {{Kermit: Guided Long Read Assembly using Coloured Overlap Graphs}}, booktitle = {18th International Workshop on Algorithms in Bioinformatics (WABI 2018)}, pages = {11:1--11:11}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-082-8}, ISSN = {1868-8969}, year = {2018}, volume = {113}, editor = {Parida, Laxmi and Ukkonen, Esko}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2018.11}, URN = {urn:nbn:de:0030-drops-93135}, doi = {10.4230/LIPIcs.WABI.2018.11}, annote = {Keywords: Genome assembly, Linkage maps, Coloured overlap graph} }

Document

**Published in:** LIPIcs, Volume 88, 17th International Workshop on Algorithms in Bioinformatics (WABI 2017)

While long reads produced by third-generation sequencing technology from, e.g, Pacific Biosciences have been shown to increase the quality of draft genomes in repetitive regions, fundamental computational challenges remain in overcoming their high error rate and assembling them efficiently. In this paper we show that the de Bruijn graph built on the long reads can be efficiently and substantially disentangled using optical mapping data as auxiliary information. Fundamental to our approach is the use of the positional de Bruijn graph and a succinct data structure for constructing and traversing this graph. Our experimental results show that over 97.7% of directed cycles have been removed from the resulting positional de Bruijn graph as compared to its non-positional counterpart. Our results thus indicate that disentangling the de Bruijn graph using positional information is a promising direction for developing a simple and efficient assembly algorithm for long reads.

Bahar Alipanahi, Leena Salmela, Simon J. Puglisi, Martin Muggli, and Christina Boucher. Disentangled Long-Read De Bruijn Graphs via Optical Maps. In 17th International Workshop on Algorithms in Bioinformatics (WABI 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 88, pp. 1:1-1:14, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2017)

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@InProceedings{alipanahi_et_al:LIPIcs.WABI.2017.1, author = {Alipanahi, Bahar and Salmela, Leena and Puglisi, Simon J. and Muggli, Martin and Boucher, Christina}, title = {{Disentangled Long-Read De Bruijn Graphs via Optical Maps}}, booktitle = {17th International Workshop on Algorithms in Bioinformatics (WABI 2017)}, pages = {1:1--1:14}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-050-7}, ISSN = {1868-8969}, year = {2017}, volume = {88}, editor = {Schwartz, Russell and Reinert, Knut}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2017.1}, URN = {urn:nbn:de:0030-drops-76614}, doi = {10.4230/LIPIcs.WABI.2017.1}, annote = {Keywords: Positional de Bruijn graph, Genome Assembly, Long Read Data, Optical maps} }

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