Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Aligning sequences to general graphs in O(V + mE) time

Mikko Rautiainen, Tobias Marschall
doi: https://doi.org/10.1101/216127
Mikko Rautiainen
1Center for Bioinformatics, Saarland University, Saarbrücken, Germany
2Max Planck Institute for Informatics, Saarbrücken, Germany
3Saarbrücken Graduate School of Computer Science, Saarland University, Saarbrücken, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Tobias Marschall
1Center for Bioinformatics, Saarland University, Saarbrücken, Germany
2Max Planck Institute for Informatics, Saarbrücken, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

Graphs are commonly used to represent sets of sequences. Either edges or nodes can be labeled by sequences, so that each path in the graph spells a concatenated sequence. Examples include graphs to represent genome assemblies, such as string graphs and de Bruijn graphs, and graphs to represent a pan-genome and hence the genetic variation present in a population. Being able to align sequencing reads to such graphs is a key step for many analyses and its applications include genome assembly, read error correction, and variant calling with respect to a variation graph. Given the wide range of applications of this basic problem, it is surprising that algorithms with optimal runtime are, to the best of our knowledge, yet unknown. In particular, aligning sequences to cyclic graphs currently represents a challenge both in theory and practice. Here, we introduce an algorithm to compute the minimum edit distance of a sequence of length m to any path in a node-labeled directed graph (V, E) in O(|V |+m|E|) time and O(|V |) space. The corresponding alignment can be obtained in the same runtime using Embedded Image space. The time complexity depends only on the length of the sequence and the size of the graph. In particular, it does not depend on the cyclicity of the graph, or any other topological features.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Back to top
PreviousNext
Posted November 08, 2017.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Aligning sequences to general graphs in O(V + mE) time
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Aligning sequences to general graphs in O(V + mE) time
Mikko Rautiainen, Tobias Marschall
bioRxiv 216127; doi: https://doi.org/10.1101/216127
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
Aligning sequences to general graphs in O(V + mE) time
Mikko Rautiainen, Tobias Marschall
bioRxiv 216127; doi: https://doi.org/10.1101/216127

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (2416)
  • Biochemistry (4774)
  • Bioengineering (3319)
  • Bioinformatics (14626)
  • Biophysics (6617)
  • Cancer Biology (5156)
  • Cell Biology (7402)
  • Clinical Trials (138)
  • Developmental Biology (4340)
  • Ecology (6858)
  • Epidemiology (2057)
  • Evolutionary Biology (9876)
  • Genetics (7328)
  • Genomics (9496)
  • Immunology (4534)
  • Microbiology (12631)
  • Molecular Biology (4919)
  • Neuroscience (28206)
  • Paleontology (198)
  • Pathology (802)
  • Pharmacology and Toxicology (1380)
  • Physiology (2012)
  • Plant Biology (4473)
  • Scientific Communication and Education (974)
  • Synthetic Biology (1295)
  • Systems Biology (3903)
  • Zoology (722)