Statistical Methods and Software for Substance Use and Dependence Genetic Research

Curr Genomics. 2019 Apr;20(3):172-183. doi: 10.2174/1389202920666190617094930.

Abstract

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.

Keywords: Association analysis; GCTA; Interaction analysis; Linkage analysis; Meta-analysis; Substance dependence.

Publication types

  • Review