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Haplotype-aware graph indexes

Authors Jouni Sirén , Erik Garrison , Adam M. Novak , Benedict J. Paten , Richard Durbin

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Author Details

Jouni Sirén
  • University of California, Santa Cruz, USA , Wellcome Sanger Institute, Hinxton, UK
Erik Garrison
  • Wellcome Sanger Institute, Hinxton, UK
Adam M. Novak
  • University of California, Santa Cruz, USA
Benedict J. Paten
  • University of California, Santa Cruz, USA
Richard Durbin
  • Department of Genetics, University of Cambridge, UK , Wellcome Sanger Institute, Hinxton, UK

Funding

  • Sirén, Jouni: Funded by Wellcome Trust grant WT206194, the National Institutes of Health (5U41HG007234, 1U01HL137183-01), and the W. M. Keck Foundation (DT06172015)
  • Garrison, Erik: Funded by Wellcome Trust grant WT206194.
  • Novak, Adam M.: Funded by the National Institutes of Health (5U41HG007234, 1U01HL137183-01) and the W. M. Keck Foundation (DT06172015)
  • Paten, Benedict J.: Funded by the National Institutes of Health (5U41HG007234, 1U01HL137183-01) and the W. M. Keck Foundation (DT06172015)
  • Durbin, Richard: Funded by Wellcome Trust grant WT206194.

Cite AsGet BibTex

Jouni Sirén, Erik Garrison, Adam M. Novak, Benedict J. Paten, and Richard Durbin. Haplotype-aware graph indexes. In 18th International Workshop on Algorithms in Bioinformatics (WABI 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 113, pp. 4:1-4:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
https://doi.org/10.4230/LIPIcs.WABI.2018.4

Abstract

The variation graph toolkit (VG) represents genetic variation as a graph. Each path in the graph is a potential haplotype, though most paths are unlikely recombinations of true haplotypes. We augment the VG model with haplotype information to identify which paths are more likely to be correct. For this purpose, we develop a scalable implementation of the graph extension of the positional Burrows-Wheeler transform. We demonstrate the scalability of the new implementation by indexing the 1000 Genomes Project haplotypes. We also develop an algorithm for simplifying variation graphs for k-mer indexing without losing any k-mers in the haplotypes.

Subject Classification

ACM Subject Classification
  • Theory of computation → Pattern matching
  • Theory of computation → Data compression
  • Applied computing → Computational genomics
Keywords
  • FM-indexes
  • variation graphs
  • haplotypes

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Supplementary Materials

References

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