Dec 15, 2017

Sequence variation aware genome references and read mapping with the variation graph toolkit

BioRxiv : the Preprint Server for Biology
Erik GarrisonRichard Durbin

Abstract

Reference genomes guide our interpretation of DNA sequence data. However, conventional linear references are fundamentally limited in that they represent only one version of each locus, whereas the population may contain multiple variants. When the reference represents an individual's genome poorly, it can impact read mapping and introduce bias. Variation graphs are bidirected DNA sequence graphs that compactly represent genetic variation, including large scale structural variation such as inversions and duplications. Equivalent structures are produced by de novo genome assemblers. Here we present vg, a toolkit of computational methods for creating, manipulating, and utilizing these structures as references at the scale of the human genome. vg provides an efficient approach to mapping reads onto arbitrary variation graphs using generalized compressed suffix arrays, with improved accuracy over alignment to a linear reference, creating data structures to support downstream variant calling and genotyping. These capabilities make using variation graphs as reference structures for DNA sequencing practical at the scale of vertebrate genomes, or at the topological complexity of new species assemblies.

  • References
  • Citations

References

  • We're still populating references for this paper, please check back later.
  • References
  • Citations

Citations

  • This paper may not have been cited yet.

Mentioned in this Paper

Vertebrates
Genome
Sequence Determinations, DNA
Structure
Downstream
Species
Locus
Suffix brand of benzoylprop-ethyl
Genome, Human
Genotype Determination

About this Paper

Related Feeds

BioRxiv & MedRxiv Preprints

BioRxiv and MedRxiv are the preprint servers for biology and health sciences respectively, operated by Cold Spring Harbor Laboratory. Here are the latest preprint articles (which are not peer-reviewed) from BioRxiv and MedRxiv.

Related Papers

BioRxiv : the Preprint Server for Biology
Mikko Rautiainen, Tobias Marschall
Methods in Molecular Biology
Pauline C Ng, Ewen F Kirkness
© 2020 Meta ULC. All rights reserved