Fast characterization of segmental duplications in genome assemblies
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bty586.pdf
Description
Published version
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430.96 KB
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Checksum (MD5)
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Author(s)
Numanagic, Ibrahim
Gokkaya, Alim S.
Zhang, Lillian
Berger Leighton, Bonnie
Alkan, Can
Hach, Faraz
Date Issued
September 8, 2018
Journal
Bioinformatics
Publisher
Oxford University Press
Citation
Numanagic, Ibrahim et al. "Fast characterization of segmental duplications in genome assemblies." Bioinformatics 34, 17 (2018) : i706–i714 © 2018 The Author(s)
Version
Final published version
Abstract
Segmental duplications (SDs) or low-copy repeats, are segments of DNA > 1 Kbp with high sequence identity that are copied to other regions of the genome. SDs are among the most important sources of evolution, a common cause of genomic structural variation and several are associated with diseases of genomic origin including schizophrenia and autism. Despite their functional importance, SDs present one of the major hurdles for de novo genome assembly due to the ambiguity they cause in building and traversing both state-of-the-art overlap-layout-consensus and de Bruijn graphs. This causes SD regions to be misassembled, collapsed into a unique representation, or completely missing from assembled reference genomes for various organisms. In turn, this missing or incorrect information limits our ability to fully understand the evolution and the architecture of the genomes. Despite the essential need to accurately characterize SDs in assemblies, there has been only one tool that was developed for this purpose, called Whole-Genome Assembly Comparison (WGAC); its primary goal is SD detection. WGAC is comprised of several steps that employ different tools and custom scripts, which makes this strategy difficult and time consuming to use. Thus there is still a need for algorithms to characterize within-assembly SDs quickly, accurately, and in a user friendly manner.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Mathematics
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Creative Commons Attribution NonCommercial License 4.0
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DOI of Published Version
https://doi.org/10.1093/bioinformatics/bty586
