Kermit: Guided Long Read Assembly using Coloured Overlap Graphs

Authors Riku Walve , Pasi Rastas, Leena Salmela



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Author Details

Riku Walve
  • Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, Finland
Pasi Rastas
  • Institute of Biotechnology, University of Helsinki, Helsinki, Finland
Leena Salmela
  • Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, Finland

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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)
https://doi.org/10.4230/LIPIcs.WABI.2018.11

Abstract

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.

Subject Classification

ACM Subject Classification
  • Applied computing → Sequencing and genotyping technologies
  • Mathematics of computing → Graph theory
Keywords
  • Genome assembly
  • Linkage maps
  • Coloured overlap graph

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