ExpansionHunter Denovo: A computational method for locating known and novel repeat expansions in short-read sequencing data
Publication date
2020-04-28
Authors
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.
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Document Type
Article
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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.
Keywords
Fragile X syndrome, Friedreich ataxia, Genome-wide analysis, Huntington disease, Myotonic dystrophy type 1, Repeat expansions, Short tandem repeats, Whole-genome sequencing data, Fragile X Syndrome/genetics, Humans, Myotonic Dystrophy/genetics, Case-Control Studies, Whole Genome Sequencing, DNA Repeat Expansion, Huntington Disease/genetics, High-Throughput Nucleotide Sequencing, Software, Friedreich Ataxia/genetics, Microsatellite Repeats, Genetics, Ecology, Evolution, Behavior and Systematics, Cell Biology, Research Support, Non-U.S. Gov't, Journal Article
Citation
Dolzhenko, E, Bennett, M F, Richmond, P A, Trost, B, Chen, S, Van Vugt, J J F A, Nguyen, C, Narzisi, G, Gainullin, V G, Gross, A M, Lajoie, B R, Taft, R J, Wasserman, W W, Scherer, S W, Veldink, J H, Bentley, D R, Yuen, R K C, Bahlo, M & Eberle, M A 2020, 'ExpansionHunter Denovo : A computational method for locating known and novel repeat expansions in short-read sequencing data', Genome Biology, vol. 21, no. 1, 102. https://doi.org/10.1186/s13059-020-02017-z