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Current Genomics

Editor-in-Chief

ISSN (Print): 1389-2029
ISSN (Online): 1875-5488

Review Article

Statistical Methods and Software for Substance Use and Dependence Genetic Research

Author(s): Tongtong Lan, Bo Yang, Xuefen Zhang, Tong Wang* and Qing Lu*

Volume 20, Issue 3, 2019

Page: [172 - 183] Pages: 12

DOI: 10.2174/1389202920666190617094930

Price: $65

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.

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