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ExpansionHunter Denovo: A computational method for locating known and novel repeat expansions in short-read sequencing data

Title: ExpansionHunter Denovo: A computational method for locating known and novel repeat expansions in short-read sequencing data
Authors: Dolzhenko, E; Bennett, MF; Richmond, PA; Trost, B; Chen, S; Van Vugt, JJFA; Nguyen, C; Narzisi, G; Gainullin, VG; Gross, AM; Lajoie, BR; Taft, RJ; Wasserman, WW; Scherer, SW; Veldink, JH; Bentley, DR; Yuen, RKC; Bahlo, M; Eberle, MA
Publisher Information: BMC
Publication Year: 2020
Collection: The University of Melbourne: Digital Repository
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.
Document Type: article in journal/newspaper
Language: English
ISSN: 1474-7596
Relation: https://hdl.handle.net/11343/246361
Availability: https://hdl.handle.net/11343/246361
Rights: https://creativecommons.org/licenses/by/4.0 ; CC BY
Accession Number: edsbas.9D90D71C
Database: BASE