Open AccessSequence tube maps: making graph genomes intuitive to commuters
Author(s) -
Wolfgang Beyer,
Adam M. Novak,
Glenn Hickey,
Jeffrey Chan,
Vanessa Y. Tan,
Benedict Paten,
Daniel R. Zerbino
Publication year - 2019
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btz597
Subject(s) - sequence (biology) , graph , computer science , theoretical computer science , combinatorics , computational biology , biology , genetics , mathematics
Compared to traditional haploid reference genomes, graph genomes are an efficient and compact data structure for storing multiple genomic sequences, for storing polymorphisms or for mapping sequencing reads with greater sensitivity. Further, graphs are well-studied computer science objects that can be efficiently analyzed. However, their adoption in genomic research is slow, in part because of the cognitive difficulty in interpreting graphs.
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