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ExpansionHunter Denovo: a computational method for locating known and novel repeat expansions in short-read sequencing data Dolzhenko, Egor; Bennett, Mark F.; Richmond, Phillip A.; Trost, Brett; Chen, Sai; van Vugt, Joke J. F. A.; Nguyen, Charlotte; Narzisi, Giuseppe; Gainullin, Vladimir G.; Gross, Andrew M.; et al.
Abstract
Repeat expansions are responsible for over 40 monogenic disorders, and undoubtedly more pathogenic repeat expansions remain to be discovered. Existing methods for detecting repeat expansions in short-read sequencing data require predefined repeat catalogs. Recent discoveries emphasize the need for methods that do not require pre-specified candidate repeats. To address this need, we introduce ExpansionHunter Denovo, an efficient catalog-free method for genome-wide repeat expansion detection. Analysis of real and simulated data shows that our method can identify large expansions of 41 out of 44 pathogenic repeats, including nine recently reported non-reference repeat expansions not discoverable via existing methods.
Item Metadata
Title |
ExpansionHunter Denovo: a computational method for locating known and novel repeat expansions in short-read sequencing data
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Creator |
Dolzhenko, Egor; Bennett, Mark F.; Richmond, Phillip A.; Trost, Brett; Chen, Sai; van Vugt, Joke J. F. A.; Nguyen, Charlotte; Narzisi, Giuseppe; Gainullin, Vladimir G.; Gross, Andrew M.; Lajoie, Bryan R.; Taft, Ryan J.; Wasserman, Wyeth W.; Scherer, Stephen W.; Veldink, Jan H.; Bentley, David R.; Yuen, Ryan K. C.; Bahlo, Melanie; Eberle, Michael A.
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Contributor | |
Publisher |
BioMed Central
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Date Issued |
2020-04-28
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Description |
Repeat expansions are responsible for over 40 monogenic disorders, and undoubtedly more pathogenic repeat expansions remain to be discovered. Existing methods for detecting repeat expansions in short-read sequencing data require predefined repeat catalogs. Recent discoveries emphasize the need for methods that do not require pre-specified candidate repeats. To address this need, we introduce ExpansionHunter Denovo, an efficient catalog-free method for genome-wide repeat expansion detection. Analysis of real and simulated data shows that our method can identify large expansions of 41 out of 44 pathogenic repeats, including nine recently reported non-reference repeat expansions not discoverable via existing methods.
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Subject | |
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Language |
eng
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Date Available |
2020-04-28
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution 4.0 International (CC BY 4.0)
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DOI |
10.14288/1.0390018
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URI | |
Affiliation | |
Citation |
Genome Biology. 2020 Apr 28;21(1):102
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Publisher DOI |
10.1186/s13059-020-02017-z
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Peer Review Status |
Reviewed
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Scholarly Level |
Faculty
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Copyright Holder |
The Author(s)
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DSpace
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Item Media
Item Citations and Data
Rights
Attribution 4.0 International (CC BY 4.0)