Journal article

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

Egor Dolzhenko, Mark F Bennett, Phillip A Richmond, Brett Trost, Sai Chen, Joke JFA van Vugt, Charlotte Nguyen, Giuseppe Narzisi, Vladimir G Gainullin, Andrew M Gross, Bryan R Lajoie, Ryan J Taft, Wyeth W Wasserman, Stephen W Scherer, Jan H Veldink, David R Bentley, Ryan KC Yuen, Melanie Bahlo, Michael A Eberle

Genome Biology | BMC | Published : 2020

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 discoverabl..

View full abstract

Grants

Awarded by Australian National Health and Medical Research Council (NHMRC)


Awarded by NHMRC Senior Research Fellowship


Awarded by European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme


Funding Acknowledgements

PAR was funded by the BC Children's Hospital Research Institute Graduate Student Scholarship, with computational infrastructure support from the University of British Columbia's Advanced Research Computing. BT was funded by the Canadian Institutes for Health Research Banting Postdoctoral Fellowship and the Canadian Open Neuroscience Platform Research Scholar Award. MB was supported by an Australian National Health and Medical Research Council (NHMRC) Program Grant (GNT1054618) and an NHMRC Senior Research Fellowship (GNT1102971). Additional funding support was provided through the Victorian State Government Operational Infrastructure Support and Australian Government NHMRC IRIISS. This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 772376 -EScORIAL). RKCY was supported by the University of Toronto's McLaughlin Centre Accelerator Grant and the Nancy E.T. Fahrner Award. CN was supported by the Restracomp Award from The Hospital for Sick Children.