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Statistical Methods and Software for Substance Use and Dependence Genetic Research

BACKGROUND: Substantial substance use disorders and related health conditions emerged dur-ing the mid-20th century and continue to represent a remarkable 21st century global burden of disease. This burden is largely driven by the substance-dependence process, which is a complex process and is influe...

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Detalles Bibliográficos
Autores principales: Lan, Tongtong, Yang, Bo, Zhang, Xuefen, Wang, Tong, Lu, Qing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bentham Science Publishers 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6935956/
https://www.ncbi.nlm.nih.gov/pubmed/31929725
http://dx.doi.org/10.2174/1389202920666190617094930
Descripción
Sumario:BACKGROUND: Substantial substance use disorders and related health conditions emerged dur-ing the mid-20th century and continue to represent a remarkable 21st century global burden of disease. This burden is largely driven by the substance-dependence process, which is a complex process and is influenced by both genetic and environmental factors. During the past few decades, a great deal of pro-gress has been made in identifying genetic variants associated with Substance Use and Dependence (SUD) through linkage, candidate gene association, genome-wide association and sequencing studies. METHODS: Various statistical methods and software have been employed in different types of SUD ge-netic studies, facilitating the identification of new SUD-related variants. CONCLUSION: In this article, we review statistical methods and software that are currently available for SUD genetic studies, and discuss their strengths and limitations.