ExpansionHunter Denovo: a computational method for locating known and novel repeat expansions in short-read sequencing data
Analysis of real and simulated data shows that the ExpansionHunter Denovo 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.
Abstract
<jats:title>Abstract</jats:title> <jats:p>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.</jats:p>