Comprehensive identification of transposable element insertions using multiple sequencing technologies

Identification of transposable element (TE) insertions from whole genome sequencing data remains challenging. Here the authors developed a comprehensive TE insertion detection algorithm xTea that can be applied to both short-read and long-read sequencing data.

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Auteurs principaux: Chong Chu, Rebeca Borges-Monroy, Vinayak V. Viswanadham, Soohyun Lee, Heng Li, Eunjung Alice Lee, Peter J. Park
Format: article
Langue:EN
Publié: Nature Portfolio 2021
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Accès en ligne:https://doaj.org/article/e8c2845aa0574d878ee04dbda688b8f8
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Résumé:Identification of transposable element (TE) insertions from whole genome sequencing data remains challenging. Here the authors developed a comprehensive TE insertion detection algorithm xTea that can be applied to both short-read and long-read sequencing data.