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Graph genomes

From Figure 2, Schatz et al. Genome Biology 2012;13(4):243.

The first reference genome sequences were entirely linear from a single or few individuals, but such a representation is not sufficient for encompassing all of the genomic variation present in a population. The human reference GRCh37 adopted a graph-based representation, by introducing the concept of alternative loci, which was expanded in GRCh38. Uptake of these graphical representations has been slow, in part because of a lack of tools to process the data in this form. 


Genome Biology is accepting submissions for an article collection of tools for graph genomes and related pan-genome analysis. There is no submission deadline, and articles will not be held for publication together: individual articles will be published when they are ready. The final collection will be accessible via a dedicated web page in our special collections catalog and highlighted on the main Genome Biology web page.


The collection will be guest edited by Michael Schatz (Johns Hopkins University, USA). He will have an advisory role to guide the scope of the collection and provide advice on content, but will not be involved in the editorial decision making on all papers submitted. 


Authors are invited to submit any methods relevant to the construction and analysis of graph-based genome representations, or related to the new standards or data structures required for representing collections of genomes.
To submit, please use our online submission system and indicate in your cover letter that you would like the manuscript to be considered for the ‘Graph genomes’ collection. If you would like to inquire about the suitability of a manuscript for consideration, please email a pre-submission inquiry to editorial@genomebiology.com.


  1. The practical use of graph-based reference genomes depends on the ability to align reads to them. Performing substring queries to paths through these graphs lies at the core of this task. The combination of in...

    Authors: Tom Mokveld, Jasper Linthorst, Zaid Al-Ars, Henne Holstege and Marcel Reinders

    Citation: Genome Biology 2020 21:65

    Content type: Method

    Published on:

  2. Structural variants (SVs) remain challenging to represent and study relative to point mutations despite their demonstrated importance. We show that variation graphs, as implemented in the vg toolkit, provide a...

    Authors: Glenn Hickey, David Heller, Jean Monlong, Jonas A. Sibbesen, Jouni Sirén, Jordan Eizenga, Eric T. Dawson, Erik Garrison, Adam M. Novak and Benedict Paten

    Citation: Genome Biology 2020 21:35

    Content type: Method

    Published on:

  3. Accurate detection and genotyping of structural variations (SVs) from short-read data is a long-standing area of development in genomics research and clinical sequencing pipelines. We introduce Paragraph, an a...

    Authors: Sai Chen, Peter Krusche, Egor Dolzhenko, Rachel M. Sherman, Roman Petrovski, Felix Schlesinger, Melanie Kirsche, David R. Bentley, Michael C. Schatz, Fritz J. Sedlazeck and Michael A. Eberle

    Citation: Genome Biology 2019 20:291

    Content type: Method

    Published on:

  4. There is growing interest in using genetic variants to augment the reference genome into a graph genome, with alternative sequences, to improve read alignment accuracy and reduce allelic bias. While adding a v...

    Authors: Jacob Pritt, Nae-Chyun Chen and Ben Langmead

    Citation: Genome Biology 2018 19:220

    Content type: Software

    Published on: