The Polygraph: A Data Structure for Genome Alignment and Variation Detection

10 pages•Published: March 18, 2019

Masaki Fujimoto, Cole Lyman and Mark Clement

Abstract

Comparing whole genomes and finding variation is an important and difficult bioinformatic task. We present the Polygraph, a data structure for reference-free, multiple whole genome alignment that can be used to identify genomic structural variation. This data structure is built from assembled genomes and preserves the genomic structure from the assembly. It avoids the “hairball” graph structure that can occur in other graph methods such as de Bruijn graphs. The Polygraph can easily be visualized and be used for identification of structural variants. We apply the Polygraph to Escherichia coli and Saccharomyces cerevisiae for finding Structural Variants.

Keyphrases: comparative genomics, genome alignment, graph, homology, structural variants

In: Oliver Eulenstein, Hisham Al-Mubaid and Qin Ding (editors). Proceedings of 11th International Conference on Bioinformatics and Computational Biology, vol 60, pages 74-83.

Links:	https://easychair.org/publications/paper/3rmK
	https://doi.org/10.29007/txxd

BibTeX entry

@inproceedings{BiCOB2019:Polygraph_Data_Structure_Genome,
  author    = {Masaki Fujimoto and Cole Lyman and Mark Clement},
  title     = {The Polygraph: A Data Structure for Genome Alignment and Variation Detection},
  booktitle = {Proceedings of 11th International Conference on Bioinformatics and Computational Biology},
  editor    = {Oliver Eulenstein and Hisham Al-Mubaid and Qin Ding},
  series    = {EPiC Series in Computing},
  volume    = {60},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/3rmK},
  doi       = {10.29007/txxd},
  pages     = {74-83},
  year      = {2019}}

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