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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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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
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author Lan, Tongtong
Yang, Bo
Zhang, Xuefen
Wang, Tong
Lu, Qing
author_facet Lan, Tongtong
Yang, Bo
Zhang, Xuefen
Wang, Tong
Lu, Qing
author_sort Lan, Tongtong
collection PubMed
description 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.
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spelling pubmed-69359562020-01-10 Statistical Methods and Software for Substance Use and Dependence Genetic Research Lan, Tongtong Yang, Bo Zhang, Xuefen Wang, Tong Lu, Qing Curr Genomics Article 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. Bentham Science Publishers 2019-04 2019-04 /pmc/articles/PMC6935956/ /pubmed/31929725 http://dx.doi.org/10.2174/1389202920666190617094930 Text en © 2019 Bentham Science Publishers https://creativecommons.org/licenses/by-nc/4.0/legalcode This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/legalcode), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
spellingShingle Article
Lan, Tongtong
Yang, Bo
Zhang, Xuefen
Wang, Tong
Lu, Qing
Statistical Methods and Software for Substance Use and Dependence Genetic Research
title Statistical Methods and Software for Substance Use and Dependence Genetic Research
title_full Statistical Methods and Software for Substance Use and Dependence Genetic Research
title_fullStr Statistical Methods and Software for Substance Use and Dependence Genetic Research
title_full_unstemmed Statistical Methods and Software for Substance Use and Dependence Genetic Research
title_short Statistical Methods and Software for Substance Use and Dependence Genetic Research
title_sort statistical methods and software for substance use and dependence genetic research
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6935956/
https://www.ncbi.nlm.nih.gov/pubmed/31929725
http://dx.doi.org/10.2174/1389202920666190617094930
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