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Connecting de Bruijn Graphs

Authors Giulia Bernardini , Huiping Chen , Inge Li Gørtz , Christoffer Krogh , Grigorios Loukides , Solon P. Pissis , Leen Stougie , Michelle Sweering

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Author Details

Giulia Bernardini
  • University of Trieste, Trieste, Italy
Huiping Chen
  • University of Birmingham, Birmingham, UK
Inge Li Gørtz
  • Technical University of Denmark, Lyngby, Denmark
Christoffer Krogh
  • Technical University of Denmark, Lyngby, Denmark
Grigorios Loukides
  • King’s College London, London, UK
Solon P. Pissis
  • CWI, Amsterdam, The Netherlands
  • Vrije Universiteit, Amsterdam, The Netherlands
Leen Stougie
  • CWI, Amsterdam, The Netherlands
  • Vrije Universiteit, Amsterdam, The Netherlands
Michelle Sweering
  • CWI, Amsterdam, The Netherlands

Funding

  • Bernardini, Giulia: Supported by the MUR - FSE REACT EU - PON R&I 2014-2020.
  • Gørtz, Inge Li: Supported by the Independent Research Fund Denmark (DFF-9131-00069B and 10.46540/3105-00302B).
  • Pissis, Solon P.: Supported by the PANGAIA and ALPACA projects that have received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreements No 872539 and 956229, respectively.
  • Stougie, Leen: Supported by the PANGAIA and ALPACA projects (grant agreements No 872539 and 956229) and by the Netherlands Organisation for Scientific Research (NWO) under projects OCENW.GROOT.2019.015 "Optimization for and with Machine Learning (OPTIMAL)" and Gravitation-grant NETWORKS-024.002.003.
  • Sweering, Michelle: Supported by the Netherlands Organisation for Scientific Research (NWO) under the Gravitation-grant NETWORKS-024.002.003.

Cite AsGet BibTex

Giulia Bernardini, Huiping Chen, Inge Li Gørtz, Christoffer Krogh, Grigorios Loukides, Solon P. Pissis, Leen Stougie, and Michelle Sweering. Connecting de Bruijn Graphs. In 35th Annual Symposium on Combinatorial Pattern Matching (CPM 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 296, pp. 6:1-6:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.CPM.2024.6

Abstract

We study the problem of making a de Bruijn graph (dBG), constructed from a collection of strings, weakly connected while minimizing the total cost of edge additions. The input graph is a dBG that can be made weakly connected by adding edges (along with extra nodes if needed) from the underlying complete dBG. The problem arises from genome reconstruction, where the dBG is constructed from a set of sequences generated from a genome sample by a sequencing experiment. Due to sequencing errors, the dBG is never Eulerian in practice and is often not even weakly connected. We show the following results for a dBG G(V,E) of order k consisting of d weakly connected components: 1) Making G weakly connected by adding a set of edges of minimal total cost is NP-hard. 2) No PTAS exists for making G weakly connected by adding a set of edges of minimal total cost (unless the unique games conjecture fails). We complement this result by showing that there does exist a polynomial-time (2-2/d)-approximation algorithm for the problem. 3) We consider a restricted version of the above problem, where we are asked to make G weakly connected by only adding directed paths between pairs of components. We show that making G weakly connected by adding d-1 such paths of minimal total cost can be done in 𝒪(k|V|α(|V|)+|E|) time, where α(⋅) is the inverse Ackermann function. This improves on the 𝒪(k|V|log(|V|)+|E|)-time algorithm proposed by Bernardini et al. [CPM 2022] for the same restricted problem. 4) An ILP formulation of polynomial size for making G Eulerian with minimal total cost.

Subject Classification

ACM Subject Classification
  • Theory of computation → Pattern matching
Keywords
  • string algorithm
  • graph algorithm
  • de Bruijn graph
  • Eulerian graph

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