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Article Details


Statistical Methods and Software for Substance Use and Dependence Genetic Research

[ Vol. 20 , Issue. 3 ]

Author(s):

Tongtong Lan, Bo Yang, Xuefen Zhang, Tong Wang* and Qing Lu*   Pages 172 - 183 ( 12 )

Abstract:


Background: Substantial substance use disorders and related health conditions emerged during 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 progress 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 genetic 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.

Keywords:

Substance dependence, linkage analysis, association analysis, interaction analysis, meta-analysis, GCTA.

Affiliation:

Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI



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