A genome-wide scan statistic framework for whole-genome sequence data analysis

Whole-genome sequencing data reveals a large number of variants for testing their associations with phenotypic traits and diseases. Here, the authors develop WGScan, a statistical method for detecting the existence and estimating the locations of the association signal at genome-wide scale.

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Detalles Bibliográficos
Autores principales: Zihuai He, Bin Xu, Joseph Buxbaum, Iuliana Ionita-Laza
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2019
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Acceso en línea:https://doaj.org/article/cfcd75a1d56442cbae3938a44f874184
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Descripción
Sumario:Whole-genome sequencing data reveals a large number of variants for testing their associations with phenotypic traits and diseases. Here, the authors develop WGScan, a statistical method for detecting the existence and estimating the locations of the association signal at genome-wide scale.